DevOps Engineer - EMEIA Infrastructure Key Responsibilities Platform Migration & Environment Design: Lead the design and build out of a new managed container environment to replace existing VM based infrastructure, primarily using Kubernetes (Client's internal Kube/EKS cluster) or another managed solution. Contribute meaningfully to the environment selection decision by weighing trade offs between managed solutions and direct control, considering maintenance overhead, operational control, and team capability. Own the migration of existing VM based workloads onto the new platform, managing sequencing, risk, and continuity of service throughout. Establish and maintain the standard workflow for deploying solutions: build locally containerise publish to Kube configure connectivity to Client internal system dependencies. Client Internal Networking & Connectivity: Configure and maintain networking between Kube and Client internal systems, including Shield, Snowflake, Client Connect, Floodgate, and other platform dependencies. Own namespace and compute provisioning on the shared Kube cluster, ensuring workloads are appropriately isolated and configured. Manage credentials, service accounts, and access controls across the full connectivity chain from container to downstream service. Act as the go to expert on how things connect within Client's internal network topology. Infrastructure Management: Own and manage cloud infrastructure across EMEIA using internal cloud tooling (and connected systems including Shield). Manage certificates, firewalls, resource pools, networking, and access controls. Ensure infrastructure is appropriately sized, resilient, and cost efficient. Maintain accurate documentation of infrastructure topology and configuration. VM Provisioning & Automation (Existing Estate): Maintain and operate existing virtual machines, primarily on RHEL, while migration to the new environment is in progress. Build and maintain standardized, repeatable provisioning processes (e.g., via Ansible, Terraform, or equivalent IaC tooling). Manage package deployment, software repositories, databases, and web servers. Own the patching and update lifecycle for managed systems. Skills & Experience Essential Proven experience in a DevOps, infrastructure, or platform engineering role. Hands on experience with Kubernetes - deploying, configuring, and operating workloads in a shared or managed cluster environment. Experience containerising applications: writing Dockerfiles, managing images, publishing to a registry, and debugging container level issues. Strong networking fundamentals: DNS, TLS/SSL certificates, firewall rules, load balancing, VPNs, and service to service connectivity. Comfort operating in environments where the architecture is still being defined - able to contribute to the decision, then execute once direction is set. Hands on experience with RHEL (or equivalent enterprise Linux) - provisioning, hardening, package management (yum/dnf), systemd services. Experience managing cloud infrastructure, ideally in an enterprise private/hybrid cloud environment. Experience with infrastructure as code or configuration management tooling (e.g., Terraform, Ansible, Puppet, or similar). Solid scripting ability in Bash and at least one higher level language (Python preferred). Experience with monitoring and observability tooling (e.g., Prometheus, Grafana, Datadog, or similar). Strong incident diagnosis skills - able to work from vague symptoms to root cause using logs, metrics, and reasoning. Comfortable working with AI generated or AI assisted codebases: reading, extending, and debugging solutions without a full traditional authorship history. Clear written and verbal communication - able to translate infrastructure complexity for non technical stakeholders. Desirable Experience with AWS or particularly EKS. Familiarity with Client's internal platform tooling: Kube, Shield, Client Connect, Floodgate, or similar. Experience integrating with Snowflake, including managing drivers, credentials, and network access. Experience with CI/CD pipelines (GitLab CI, Jenkins, GitHub Actions, or similar). Exposure to security tooling, vulnerability scanning, or compliance frameworks (e.g., CIS Benchmarks). Familiarity with secrets management tooling (Vault, CyberArk, or similar). Experience working in a regulated or enterprise environment with change management processes. We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, caste, creed, religion, gender, marital status, age, ethnic and national origin, gender identity, gender expression, sexual orientation, political orientation, disability status, protected veteran status, or any other characteristic protected by law. Wipro is committed to creating an accessible, supportive, and inclusive workplace. Reasonable accommodation will be provided to all applicants including persons with disabilities, throughout the recruitment and selection process. Accommodations must be communicated in advance of the application, where possible, and will be reviewed on an individual basis. Wipro provides equal opportunities to all and values diversity.
18/07/2026
Full time
DevOps Engineer - EMEIA Infrastructure Key Responsibilities Platform Migration & Environment Design: Lead the design and build out of a new managed container environment to replace existing VM based infrastructure, primarily using Kubernetes (Client's internal Kube/EKS cluster) or another managed solution. Contribute meaningfully to the environment selection decision by weighing trade offs between managed solutions and direct control, considering maintenance overhead, operational control, and team capability. Own the migration of existing VM based workloads onto the new platform, managing sequencing, risk, and continuity of service throughout. Establish and maintain the standard workflow for deploying solutions: build locally containerise publish to Kube configure connectivity to Client internal system dependencies. Client Internal Networking & Connectivity: Configure and maintain networking between Kube and Client internal systems, including Shield, Snowflake, Client Connect, Floodgate, and other platform dependencies. Own namespace and compute provisioning on the shared Kube cluster, ensuring workloads are appropriately isolated and configured. Manage credentials, service accounts, and access controls across the full connectivity chain from container to downstream service. Act as the go to expert on how things connect within Client's internal network topology. Infrastructure Management: Own and manage cloud infrastructure across EMEIA using internal cloud tooling (and connected systems including Shield). Manage certificates, firewalls, resource pools, networking, and access controls. Ensure infrastructure is appropriately sized, resilient, and cost efficient. Maintain accurate documentation of infrastructure topology and configuration. VM Provisioning & Automation (Existing Estate): Maintain and operate existing virtual machines, primarily on RHEL, while migration to the new environment is in progress. Build and maintain standardized, repeatable provisioning processes (e.g., via Ansible, Terraform, or equivalent IaC tooling). Manage package deployment, software repositories, databases, and web servers. Own the patching and update lifecycle for managed systems. Skills & Experience Essential Proven experience in a DevOps, infrastructure, or platform engineering role. Hands on experience with Kubernetes - deploying, configuring, and operating workloads in a shared or managed cluster environment. Experience containerising applications: writing Dockerfiles, managing images, publishing to a registry, and debugging container level issues. Strong networking fundamentals: DNS, TLS/SSL certificates, firewall rules, load balancing, VPNs, and service to service connectivity. Comfort operating in environments where the architecture is still being defined - able to contribute to the decision, then execute once direction is set. Hands on experience with RHEL (or equivalent enterprise Linux) - provisioning, hardening, package management (yum/dnf), systemd services. Experience managing cloud infrastructure, ideally in an enterprise private/hybrid cloud environment. Experience with infrastructure as code or configuration management tooling (e.g., Terraform, Ansible, Puppet, or similar). Solid scripting ability in Bash and at least one higher level language (Python preferred). Experience with monitoring and observability tooling (e.g., Prometheus, Grafana, Datadog, or similar). Strong incident diagnosis skills - able to work from vague symptoms to root cause using logs, metrics, and reasoning. Comfortable working with AI generated or AI assisted codebases: reading, extending, and debugging solutions without a full traditional authorship history. Clear written and verbal communication - able to translate infrastructure complexity for non technical stakeholders. Desirable Experience with AWS or particularly EKS. Familiarity with Client's internal platform tooling: Kube, Shield, Client Connect, Floodgate, or similar. Experience integrating with Snowflake, including managing drivers, credentials, and network access. Experience with CI/CD pipelines (GitLab CI, Jenkins, GitHub Actions, or similar). Exposure to security tooling, vulnerability scanning, or compliance frameworks (e.g., CIS Benchmarks). Familiarity with secrets management tooling (Vault, CyberArk, or similar). Experience working in a regulated or enterprise environment with change management processes. We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, caste, creed, religion, gender, marital status, age, ethnic and national origin, gender identity, gender expression, sexual orientation, political orientation, disability status, protected veteran status, or any other characteristic protected by law. Wipro is committed to creating an accessible, supportive, and inclusive workplace. Reasonable accommodation will be provided to all applicants including persons with disabilities, throughout the recruitment and selection process. Accommodations must be communicated in advance of the application, where possible, and will be reviewed on an individual basis. Wipro provides equal opportunities to all and values diversity.
StormHarvester helps wastewater utilities predict and prevent issues like flooding and pollution before they happen, protecting communities and reducing costs. We are the market leader in this space. At its core, StormHarvester's advanced anomaly detection system analyses data from thousands of sensors, turning it into precise, actionable insights that drive smarter decisions. About the role Our products deliver on real-world issues, solving water company and industry problems with existing and new infrastructure that is critical to the environment, economy and everyday living. We are primarily data driven with domain expertise delivering insights to water networks and assets using analytics, presentation, machine learning and AI that is SaaS and cloud based. We are building on our existing team to onward develop our existing products, and continue growing our customer offerings, base and revenues. Working with and as part of the internal customer development and delivery team, help enhance the success of our customer deployments and product utilisation. You will do this in both a proactive and reactive mode, where internally we work to enhance product delivery and address any potential problems, and also to respond to customer queries or issues as they are raised. This is a technical role, requiring good teamwork and communication skills working across internal development and delivery teams, customer account management, and our customers. You will need to be able to articulate status in terms of delivery to customers, and what is required from other teams to help you make your role successful. The work is mainly helping customers successfully utilise the StormHarvester product in guiding them to grow their supported network elements, make changes/updates/enhancements to existing configurations, and helping fix/address issues when they occur. Job requirements ESSENTIAL CRITERIA: Degree level education in a relevant discipline or equivalent experience Min 12 months experience and familiarity with development & delivery in a developer role Experienced in at least one of the main cloud technologies - AWS, Azure, RedHat, GCP, IBM Cloud Strong working knowledge of Linux Strong work ethic with an understanding that we are in a growth phase with lots of opportunities to make improvements Ability to review and provide feedback as needed to the rest of the team on areas of improvements and updates Can-do, problem-solving mindset DESIRABLE CRITERIA: Experience of AWS services Experience implementing cloud infrastructure and networking required to host services, including storage, firewall and network configuration Experience in deploying serverless functions e.g. AWS Lambda Experience of Agile Scrum, Lean or Kanban using JIRA, or similar agile tracking tools Job responsibilities Capture, document, estimate and prioritise sets of work in an Agile team environment, then implement and test these as part of delivery Be part of onboarding new customers Addressing bugs/changes, and problem solving issues as part of a wider team Build in as needed custom features while seeking to maximise reuse and productisation of features Troubleshoot configuration, environmental and software issues and help identify solutions to restore customer service Implementation and delivery of designs/fixes as part of a continuous delivery mechanism through to live deployments Advocate for additional tooling or processes with a view to optimisation and improvement Automation of processes Prepare and present potential delivery options including estimating, costing and prioritizing As part of a team, plan for future developments including contributions to team structures, roles and requirements with an awareness of all existing and future customers in mind Understand the deployment, sites and sensors under management across our customers Look for opportunities for improvements in service delivery and product use Take ownership for the product performance and behaviours in customer deployments across configuration and infrastructure AWS Infrastructure Management: Design, implement, and manage AWS cloud infrastructure. Optimize AWS resources to ensure cost-effective and scalable solutions. Monitor and maintain AWS services including EC2, S3, RDS, Lambda, and more. Free parking at our Belfast office Private medical and dental insurance 24 days+ annual leave Electric vehicle scheme Tech Scheme Cycle Scheme Join us in shaping the future of water and sustainability.
16/07/2026
Full time
StormHarvester helps wastewater utilities predict and prevent issues like flooding and pollution before they happen, protecting communities and reducing costs. We are the market leader in this space. At its core, StormHarvester's advanced anomaly detection system analyses data from thousands of sensors, turning it into precise, actionable insights that drive smarter decisions. About the role Our products deliver on real-world issues, solving water company and industry problems with existing and new infrastructure that is critical to the environment, economy and everyday living. We are primarily data driven with domain expertise delivering insights to water networks and assets using analytics, presentation, machine learning and AI that is SaaS and cloud based. We are building on our existing team to onward develop our existing products, and continue growing our customer offerings, base and revenues. Working with and as part of the internal customer development and delivery team, help enhance the success of our customer deployments and product utilisation. You will do this in both a proactive and reactive mode, where internally we work to enhance product delivery and address any potential problems, and also to respond to customer queries or issues as they are raised. This is a technical role, requiring good teamwork and communication skills working across internal development and delivery teams, customer account management, and our customers. You will need to be able to articulate status in terms of delivery to customers, and what is required from other teams to help you make your role successful. The work is mainly helping customers successfully utilise the StormHarvester product in guiding them to grow their supported network elements, make changes/updates/enhancements to existing configurations, and helping fix/address issues when they occur. Job requirements ESSENTIAL CRITERIA: Degree level education in a relevant discipline or equivalent experience Min 12 months experience and familiarity with development & delivery in a developer role Experienced in at least one of the main cloud technologies - AWS, Azure, RedHat, GCP, IBM Cloud Strong working knowledge of Linux Strong work ethic with an understanding that we are in a growth phase with lots of opportunities to make improvements Ability to review and provide feedback as needed to the rest of the team on areas of improvements and updates Can-do, problem-solving mindset DESIRABLE CRITERIA: Experience of AWS services Experience implementing cloud infrastructure and networking required to host services, including storage, firewall and network configuration Experience in deploying serverless functions e.g. AWS Lambda Experience of Agile Scrum, Lean or Kanban using JIRA, or similar agile tracking tools Job responsibilities Capture, document, estimate and prioritise sets of work in an Agile team environment, then implement and test these as part of delivery Be part of onboarding new customers Addressing bugs/changes, and problem solving issues as part of a wider team Build in as needed custom features while seeking to maximise reuse and productisation of features Troubleshoot configuration, environmental and software issues and help identify solutions to restore customer service Implementation and delivery of designs/fixes as part of a continuous delivery mechanism through to live deployments Advocate for additional tooling or processes with a view to optimisation and improvement Automation of processes Prepare and present potential delivery options including estimating, costing and prioritizing As part of a team, plan for future developments including contributions to team structures, roles and requirements with an awareness of all existing and future customers in mind Understand the deployment, sites and sensors under management across our customers Look for opportunities for improvements in service delivery and product use Take ownership for the product performance and behaviours in customer deployments across configuration and infrastructure AWS Infrastructure Management: Design, implement, and manage AWS cloud infrastructure. Optimize AWS resources to ensure cost-effective and scalable solutions. Monitor and maintain AWS services including EC2, S3, RDS, Lambda, and more. Free parking at our Belfast office Private medical and dental insurance 24 days+ annual leave Electric vehicle scheme Tech Scheme Cycle Scheme Join us in shaping the future of water and sustainability.
Data Analytics & Machine Learning Engineer About StormHarvester StormHarvester helps wastewater utilities predict and prevent issues like flooding and pollution before they happen, protecting communities and reducing costs. We are the market leader in this space. At its core, StormHarvester's advanced anomaly detection system analyses data from thousands of sensors, turning it into precise, actionable insights that drive smarter decisions. About the role StormHarvester helps wastewater utilities predict and prevent issues like flooding and pollution before they happen, protecting communities and reducing costs. Our products deliver on real-world issues, solving water company and industry problems with existing and new infrastructure that is critical to the environment, economy and everyday living. We are primarily data driven with domain expertise delivering insights to water networks and assets using analytics, presentation, machine learning and AI that is SaaS and cloud based. We are building on our existing team to develop our existing products, and continue growing our customer offerings, base and revenues. The ML & Data Services team is focused on maintaining and enhancing StormHarvester's core ML capabilities, working with customers and other teams to apply new ML & data-driven solutions to meet customer's needs, and developing processes to allow customers to get the most value out of their data. This is a pragmatic and delivery-focused role in the use of data, analytics, and ML to deliver predictive outcomes for StormHarvester customers as part of our product. It will involve working with customer data, understanding and appreciating the underlying domain, carrying out analysis, and integrating or developing new techniques for implementation and delivery as part of our product offerings. This includes feature engineering, applying varying models, testing, and validation, and best practices for use for customers. You will work within a team of 6-8, but will have ownership over individual projects, while also working within the larger engineering team to test and validate any features, fixes, or updates. Job responsibilities Collaboration with stakeholders (e.g. wastewater domain experts) to understand contextual requirements of projects, to guide development of bespoke modelling approaches to address industry issues Designing scalable feature engineering and data transformation processes tailored to sewer data Development of predictive models using time series, geospatial and environmental sensor data Contributing to delivery process and development environments, including research and identifying areas of interest for further investigation Addressing bugs / changes, problem solving and support issues as part of wider engineering team Implementation, testing and delivery of designs / fixes as part of a continuous delivery mechanism through to live deployments. Qualifications A third level qualification in Data Science, Computer Science, or a data / ML-driven equivalent; 3+ years of experience in Data Science, ML Engineering, Data Analytics, or a related speciality, or equivalent knowledge; Experience with Python (Pandas, Scikit-learn or equivalent); Experience with data exploration and visualisation; Strong presentation and communication skills; Willingness to engage and work with others as part of a team with shared direction; Strong work ethic with an understanding that this is a fast-growing company with lots of opportunities to make improvements and to move quickly; Ability to review and provide feedback as needed to other teams on areas for improvements and updates; Passionate about work, output and quality; Curious and willing to onward develop and learn in ML / AI area. Desirable criteria Experience with AWS services (or transferable cloud experience) Experience modelling time series data Familiarity with Geospatial (GIS) data Familiarity with MLOps principles Familiarity and experience with agile development in delivery Experience of Continuous Integration/Development and Tooling Experience using LLMs & other AI tools in a forward thinking and ethical way. Benefits Comprehensive Private Medical insurance including dental and optical provision. Company pension scheme with 5% employer contribution and 5% employee contribution. Annual holidays of 24 days pro rata plus 1 day Birthday leave and 10 statutory holidays. Enhanced Maternity and Paternity Pay. Additional EV, Cycle, Tech & Home Scheme. Join us in shaping the future of water and sustainability.
14/07/2026
Full time
Data Analytics & Machine Learning Engineer About StormHarvester StormHarvester helps wastewater utilities predict and prevent issues like flooding and pollution before they happen, protecting communities and reducing costs. We are the market leader in this space. At its core, StormHarvester's advanced anomaly detection system analyses data from thousands of sensors, turning it into precise, actionable insights that drive smarter decisions. About the role StormHarvester helps wastewater utilities predict and prevent issues like flooding and pollution before they happen, protecting communities and reducing costs. Our products deliver on real-world issues, solving water company and industry problems with existing and new infrastructure that is critical to the environment, economy and everyday living. We are primarily data driven with domain expertise delivering insights to water networks and assets using analytics, presentation, machine learning and AI that is SaaS and cloud based. We are building on our existing team to develop our existing products, and continue growing our customer offerings, base and revenues. The ML & Data Services team is focused on maintaining and enhancing StormHarvester's core ML capabilities, working with customers and other teams to apply new ML & data-driven solutions to meet customer's needs, and developing processes to allow customers to get the most value out of their data. This is a pragmatic and delivery-focused role in the use of data, analytics, and ML to deliver predictive outcomes for StormHarvester customers as part of our product. It will involve working with customer data, understanding and appreciating the underlying domain, carrying out analysis, and integrating or developing new techniques for implementation and delivery as part of our product offerings. This includes feature engineering, applying varying models, testing, and validation, and best practices for use for customers. You will work within a team of 6-8, but will have ownership over individual projects, while also working within the larger engineering team to test and validate any features, fixes, or updates. Job responsibilities Collaboration with stakeholders (e.g. wastewater domain experts) to understand contextual requirements of projects, to guide development of bespoke modelling approaches to address industry issues Designing scalable feature engineering and data transformation processes tailored to sewer data Development of predictive models using time series, geospatial and environmental sensor data Contributing to delivery process and development environments, including research and identifying areas of interest for further investigation Addressing bugs / changes, problem solving and support issues as part of wider engineering team Implementation, testing and delivery of designs / fixes as part of a continuous delivery mechanism through to live deployments. Qualifications A third level qualification in Data Science, Computer Science, or a data / ML-driven equivalent; 3+ years of experience in Data Science, ML Engineering, Data Analytics, or a related speciality, or equivalent knowledge; Experience with Python (Pandas, Scikit-learn or equivalent); Experience with data exploration and visualisation; Strong presentation and communication skills; Willingness to engage and work with others as part of a team with shared direction; Strong work ethic with an understanding that this is a fast-growing company with lots of opportunities to make improvements and to move quickly; Ability to review and provide feedback as needed to other teams on areas for improvements and updates; Passionate about work, output and quality; Curious and willing to onward develop and learn in ML / AI area. Desirable criteria Experience with AWS services (or transferable cloud experience) Experience modelling time series data Familiarity with Geospatial (GIS) data Familiarity with MLOps principles Familiarity and experience with agile development in delivery Experience of Continuous Integration/Development and Tooling Experience using LLMs & other AI tools in a forward thinking and ethical way. Benefits Comprehensive Private Medical insurance including dental and optical provision. Company pension scheme with 5% employer contribution and 5% employee contribution. Annual holidays of 24 days pro rata plus 1 day Birthday leave and 10 statutory holidays. Enhanced Maternity and Paternity Pay. Additional EV, Cycle, Tech & Home Scheme. Join us in shaping the future of water and sustainability.
QA Engineer LOCATION: Belfast, On site Office Location: Belfast About StormHarvester StormHarvester helps wastewater utilities predict and prevent issues like flooding and pollution before they happen, protecting communities and reducing costs. We are the market leader in this space. At its core, StormHarvester's advanced anomaly detection system analyses data from thousands of sensors, turning it into precise, actionable insights that drive smarter decisions. About the role Our products deliver on real-world issues, solving water company and industry problems with existing and new infrastructure which is critical to the environment, economy and everyday living. We are primarily data driven with domain expertise delivering insights to water networks and assets using analytics, presentation, machine learning and AI that is SAAS and cloud based. We are building on our existing team to onward develop our existing products, and continue growing our customer offerings, base and revenues. We are looking for an experienced and motivated QA Engineer to lead our test strategy and execution. You will architect automation frameworks, implement scalable testing solutions, and play a key role in ensuring the delivery of high-quality, reliable software products. This is a hands on role that also involves mentorship, technical leadership, and close collaboration with DevOps, Developers, and Product teams. Essential Criteria Degree level education in a relevant discipline or equivalent experience 3+ years of experience in QA, with a strong focus on framework development. Proven expertise with test automation tools: Selenium, Cypress, Playwright, or similar. Experience working with the Angular (v16+) framework Hands on experience with scripting/programming languages like JavaScript, TypeScript, Python, or Java. Deep understanding of CI/CD pipelines and automation integration using tools like Jenkins, GitLab CI/CD, GitHub Actions. Solid grasp of RESTful APIs, JSON, and Postman or similar API testing tools. Familiarity with cloud-based testing on AWS or equivalent platforms. Strong working knowledge of Linux Strong understanding of Agile methodologies and collaborative software development environments. Desirable Criteria AWS Certification (e.g., Cloud Practitioner, Solutions Architect) is a significant advantage. ISTQB Certification or equivalent testing qualifications. Experience with cloud infrastructure and serverless testing (e.g., AWS Lambda). Familiarity with BDD tools (e.g., Cucumber, Behave). Experience using test reporting tools (e.g., Allure, ExtentReports, TestNG). Exposure to containerized environments (e.g., Docker, Kubernetes) for testing. Job responsibilities Test Automation Framework Ownership: Design and develop custom, scalable, and reusable test automation frameworks using tools such as Selenium, Cypress, Playwright, or equivalent. Standardize automation practices across teams and ensure modular, maintainable test code. End-to-End Test Automation: Create automated test suites for web, API, regression, and integration testing. Embed automated tests into CI/CD pipelines to enable continuous testing and early defect detection. Technical Leadership & Strategy: Define automation goals, best practices, and quality KPIs across the QA function. Lead test planning and reviews while mentoring junior QA engineers. Cloud & DevOps Collaboration: Collaborate with DevOps and Cloud teams to run automation on AWS based infrastructure. Leverage AWS tools (e.g., CloudWatch, Lambda, EC2) as part of the test ecosystem. Agile Delivery Support: Participate in sprint ceremonies, refine user stories with test criteria, and ensure strong collaboration with developers and product stakeholders. Documentation & Reporting: Maintain test documentation and coverage reports. Track defects and test results using tools like JIRA, TestRail, or similar. Job benefits Free parking at our Belfast office Private medical and dental insurance 24 days+ annual leave Electric vehicle scheme Cycle Scheme, Tech Scheme Life Cover
14/07/2026
Full time
QA Engineer LOCATION: Belfast, On site Office Location: Belfast About StormHarvester StormHarvester helps wastewater utilities predict and prevent issues like flooding and pollution before they happen, protecting communities and reducing costs. We are the market leader in this space. At its core, StormHarvester's advanced anomaly detection system analyses data from thousands of sensors, turning it into precise, actionable insights that drive smarter decisions. About the role Our products deliver on real-world issues, solving water company and industry problems with existing and new infrastructure which is critical to the environment, economy and everyday living. We are primarily data driven with domain expertise delivering insights to water networks and assets using analytics, presentation, machine learning and AI that is SAAS and cloud based. We are building on our existing team to onward develop our existing products, and continue growing our customer offerings, base and revenues. We are looking for an experienced and motivated QA Engineer to lead our test strategy and execution. You will architect automation frameworks, implement scalable testing solutions, and play a key role in ensuring the delivery of high-quality, reliable software products. This is a hands on role that also involves mentorship, technical leadership, and close collaboration with DevOps, Developers, and Product teams. Essential Criteria Degree level education in a relevant discipline or equivalent experience 3+ years of experience in QA, with a strong focus on framework development. Proven expertise with test automation tools: Selenium, Cypress, Playwright, or similar. Experience working with the Angular (v16+) framework Hands on experience with scripting/programming languages like JavaScript, TypeScript, Python, or Java. Deep understanding of CI/CD pipelines and automation integration using tools like Jenkins, GitLab CI/CD, GitHub Actions. Solid grasp of RESTful APIs, JSON, and Postman or similar API testing tools. Familiarity with cloud-based testing on AWS or equivalent platforms. Strong working knowledge of Linux Strong understanding of Agile methodologies and collaborative software development environments. Desirable Criteria AWS Certification (e.g., Cloud Practitioner, Solutions Architect) is a significant advantage. ISTQB Certification or equivalent testing qualifications. Experience with cloud infrastructure and serverless testing (e.g., AWS Lambda). Familiarity with BDD tools (e.g., Cucumber, Behave). Experience using test reporting tools (e.g., Allure, ExtentReports, TestNG). Exposure to containerized environments (e.g., Docker, Kubernetes) for testing. Job responsibilities Test Automation Framework Ownership: Design and develop custom, scalable, and reusable test automation frameworks using tools such as Selenium, Cypress, Playwright, or equivalent. Standardize automation practices across teams and ensure modular, maintainable test code. End-to-End Test Automation: Create automated test suites for web, API, regression, and integration testing. Embed automated tests into CI/CD pipelines to enable continuous testing and early defect detection. Technical Leadership & Strategy: Define automation goals, best practices, and quality KPIs across the QA function. Lead test planning and reviews while mentoring junior QA engineers. Cloud & DevOps Collaboration: Collaborate with DevOps and Cloud teams to run automation on AWS based infrastructure. Leverage AWS tools (e.g., CloudWatch, Lambda, EC2) as part of the test ecosystem. Agile Delivery Support: Participate in sprint ceremonies, refine user stories with test criteria, and ensure strong collaboration with developers and product stakeholders. Documentation & Reporting: Maintain test documentation and coverage reports. Track defects and test results using tools like JIRA, TestRail, or similar. Job benefits Free parking at our Belfast office Private medical and dental insurance 24 days+ annual leave Electric vehicle scheme Cycle Scheme, Tech Scheme Life Cover
Customer Data Analyst (min 3 years experience). Location: Belfast (On site). About StormHarvester StormHarvester helps wastewater utilities predict and prevent issues like flooding and pollution before they happen, protecting communities and reducing costs. We are the market leader in this space. At its core, StormHarvester's advanced anomaly detection system analyzes data from thousands of sensors, turning it into precise, actionable insights that drive smarter decisions. About the role Our products address real world challenges faced by water companies and industries, utilizing existing and new infrastructure that is critical to the environment, economy and everyday life. We are primarily data driven, employing domain expertise to deliver insights to water networks and assets using analytics, presentation, machine learning and AI in a SAAS and cloud based platform. We are building on our existing team to further develop our current product and continue to grow our customer base and revenues. Working with the bespoke StormHarvester data toolset, this position calls for critical thinking, data analysis, a solution oriented approach, and a deep understanding of what constitutes "good" data for water utility sewers. The role is crucial for bridging internal and external teams to ensure service delivery to customers meets high standards. You will become familiar with the waste water network for our customers, making judgments and assessments regarding how best to represent the data in conjunction with our customers and within StormHarvester. You will actively review and enact changes to system outputs and models to support customers in their waste water network management. Job Requirements & Criteria Customer Analysis Daily reviews of outputs delivered to customers. Assessment of alerts and potential changes. Quality assessment and cleaning of data. Creation of new models and updates to existing models. Preparation of customer reports on service delivery as required. Internal Reporting Prepare internal reports and feedback on current product behaviours across multiple customers and assets. Ticket Management Raise internal tickets for work and follow up on their implementation. Input into AI back end/StormHarvester Toolset Innovation Seek opportunities for service improvement and enhanced efficiencies. Identify tooling improvements for useful new tools and processes. To perform the role effectively, familiarity with the following is required The wastewater network, components, and processes. Varying behaviours at individual nodes and across the network. The StormHarvester Products. The StormHarvester Tools for understanding and predicting behaviours.The StormHarvester customers and SLAs. Account Management and StormHarvester responsibilities and commitments. StormHarvester customer interfaces. Alerting and alarming for sites and customers. Predictive models and parameters. Essential Criteria Demonstrable analytical capabilities. Ability to interpret graphs with respect to actual versus desired behaviours. Experience in data analysis. Strong verbal and written communication skills. Familiarity with Microsoft Excel, PowerPoint, Teams and Word. Good client relationship skills. Desirable Criteria Experience in the water industry, water utility or related domain. Civil engineering appreciation or experience. Use of business analytical tools. Ability to create macros or use data analysis tooling. Experience working in technical teams. Project management experience. Job Responsibilities Review alerting outputs and make necessary changes based on behavioural judgments for individual customers. Assess when predicted behaviors are deemed unacceptable and/or need improvement. Use StormHarvester tooling to review and assess behaviors. Use StormHarvester tooling to create new behaviors and validate improvements. Use StormHarvester tooling to enable service changes or manually update outcomes. Identify behaviors or outcomes that are not 'good enough' and require additional work from teams to improve. Communicate ongoing behaviors and issues, prioritizing based on outcomes and customer requirements. Prepare internal reports and feedback on current product behaviors across multiple customers and assets. Assess outputs of new product developments and updates. Suggest enhancements that would improve behaviors and outputs. Job Benefits Comprehensive private medical insurance, including dental and optical provision. Company pension scheme with 5% employer contribution and 5% employee contribution. Annual holidays of 24 days pro rata plus 1 birthday leave and 10 statutory holidays. Enhanced maternity and paternity pay. Additional EV, cycle, tech & home scheme. Car parking close to the office.
04/07/2026
Full time
Customer Data Analyst (min 3 years experience). Location: Belfast (On site). About StormHarvester StormHarvester helps wastewater utilities predict and prevent issues like flooding and pollution before they happen, protecting communities and reducing costs. We are the market leader in this space. At its core, StormHarvester's advanced anomaly detection system analyzes data from thousands of sensors, turning it into precise, actionable insights that drive smarter decisions. About the role Our products address real world challenges faced by water companies and industries, utilizing existing and new infrastructure that is critical to the environment, economy and everyday life. We are primarily data driven, employing domain expertise to deliver insights to water networks and assets using analytics, presentation, machine learning and AI in a SAAS and cloud based platform. We are building on our existing team to further develop our current product and continue to grow our customer base and revenues. Working with the bespoke StormHarvester data toolset, this position calls for critical thinking, data analysis, a solution oriented approach, and a deep understanding of what constitutes "good" data for water utility sewers. The role is crucial for bridging internal and external teams to ensure service delivery to customers meets high standards. You will become familiar with the waste water network for our customers, making judgments and assessments regarding how best to represent the data in conjunction with our customers and within StormHarvester. You will actively review and enact changes to system outputs and models to support customers in their waste water network management. Job Requirements & Criteria Customer Analysis Daily reviews of outputs delivered to customers. Assessment of alerts and potential changes. Quality assessment and cleaning of data. Creation of new models and updates to existing models. Preparation of customer reports on service delivery as required. Internal Reporting Prepare internal reports and feedback on current product behaviours across multiple customers and assets. Ticket Management Raise internal tickets for work and follow up on their implementation. Input into AI back end/StormHarvester Toolset Innovation Seek opportunities for service improvement and enhanced efficiencies. Identify tooling improvements for useful new tools and processes. To perform the role effectively, familiarity with the following is required The wastewater network, components, and processes. Varying behaviours at individual nodes and across the network. The StormHarvester Products. The StormHarvester Tools for understanding and predicting behaviours.The StormHarvester customers and SLAs. Account Management and StormHarvester responsibilities and commitments. StormHarvester customer interfaces. Alerting and alarming for sites and customers. Predictive models and parameters. Essential Criteria Demonstrable analytical capabilities. Ability to interpret graphs with respect to actual versus desired behaviours. Experience in data analysis. Strong verbal and written communication skills. Familiarity with Microsoft Excel, PowerPoint, Teams and Word. Good client relationship skills. Desirable Criteria Experience in the water industry, water utility or related domain. Civil engineering appreciation or experience. Use of business analytical tools. Ability to create macros or use data analysis tooling. Experience working in technical teams. Project management experience. Job Responsibilities Review alerting outputs and make necessary changes based on behavioural judgments for individual customers. Assess when predicted behaviors are deemed unacceptable and/or need improvement. Use StormHarvester tooling to review and assess behaviors. Use StormHarvester tooling to create new behaviors and validate improvements. Use StormHarvester tooling to enable service changes or manually update outcomes. Identify behaviors or outcomes that are not 'good enough' and require additional work from teams to improve. Communicate ongoing behaviors and issues, prioritizing based on outcomes and customer requirements. Prepare internal reports and feedback on current product behaviors across multiple customers and assets. Assess outputs of new product developments and updates. Suggest enhancements that would improve behaviors and outputs. Job Benefits Comprehensive private medical insurance, including dental and optical provision. Company pension scheme with 5% employer contribution and 5% employee contribution. Annual holidays of 24 days pro rata plus 1 birthday leave and 10 statutory holidays. Enhanced maternity and paternity pay. Additional EV, cycle, tech & home scheme. Car parking close to the office.
We are looking for a skilled and pragmatic DevOps Engineer to own and evolve our infrastructure across the EMEIA region. This is a dual-horizon role: you will keep our existing VM-based systems healthy while leading a greenfield effort to design and build the managed environment that those solutions will migrate onto. A significant proportion of what we build is produced rapidly using AI-assisted, structured development. That means our solutions can move from idea to deployment faster than ever, and our infrastructure needs to keep pace. We need someone who thrives in a fast-moving, ambiguous environment, can absorb change quickly, and treats adaptability as a core part of the job rather than an occasional demand. The new managed environment is most likely to be based on Kube - Apple's internal Kubernetes (EKS) deployment - though the final architecture will be a team decision and remains an option for workloads requiring greater control. You will help inform that decision and then own the build out, regardless of which direction is chosen. You will work closely with data engineers, developers, and analysts, acting as the infrastructure backbone for a team that moves quickly and expects you to move with it. The role also involves working directly with third party vendors who support some of the tools being deployed, and collaborating with teams outside of EMEIA - including WorldWide - to align on standards, share solutions, and resolve cross regional dependencies. KEY RESPONSIBILITIES Lead the design and build out of a new managed container environment to replace existing VM based infrastructure - the most likely candidate is Kube (Apple's internal Kubernetes/EKS cluster), but the final decision will be made collaboratively as a team Contribute meaningfully to the environment selection decision: weigh trade offs between managed solutions (Kube) and more directly controlled alternatives considering maintenance overhead, operational control, and team capability Own the migration of existing VM based workloads onto the new platform, managing sequencing, risk, and continuity of service throughout Establish and maintain the standard workflow for deploying solutions: build locally containerise publish to Kube configure connectivity to Apple internal system dependencies Apple Internal Networking & Connectivity Configure and maintain networking between Kube and Apple's internal systems, including Shield, Snowflake, Appleconnect, Floodgate, and any other platform dependencies the team relies on Own namespace and compute provisioning on the shared Kube cluster, ensuring workloads are appropriately isolated and correctly configured Manage credentials, service accounts, and access controls across the full connectivity chain - from container to downstream service Act as the go to expert on how things connect within Apple's internal network topology Infrastructure Management Own and manage cloud infrastructure across EMEIA using internal cloud tooling (and connected systems including Shield) Manage certificates, firewalls, resource pools, networking, and access controls Ensure infrastructure is appropriately sized, resilient, and cost efficient Maintain accurate documentation of infrastructure topology and configuration Maintain and operate existing virtual machines, primarily on RHEL, while migration to the new environment is in progress Build and maintain standardised, repeatable provisioning processes (e.g. via Ansible, Terraform, or equivalent IaC tooling) Manage package deployment, software repositories, databases, and web servers Own the patching and update lifecycle for managed systems Monitoring & Reliability Implement and maintain monitoring, alerting, and observability across both the existing VM estate and the new container environment Proactively identify risks, bottlenecks, and failure patterns before they impact users Define and track appropriate SLIs/SLOs for critical services Conduct post incident reviews and drive lasting improvements Supporting AI Augmented Development A large proportion of the solutions you will support are built rapidly using structured AI assisted development - you must be comfortable working with codebases and configurations that evolve quickly, may not have deep documentation histories, and may have been substantially generated with AI tooling Provide the infrastructure scaffold that allows AI assisted solutions to move from local development to production reliably and safely Be a pragmatic partner to developers: unblock deployment quickly, catch infrastructure level risks early, and help establish patterns that make rapid iteration safe at scale Actively use AI tools (e.g. Claude, Copilot, or similar) to accelerate your own work: writing scripts, diagnosing issues, generating runbooks, reviewing configurations Diagnosis & Incident Response Take ownership of vague or ambiguous production issues (e.g. "it's running slow", "the server keeps falling over") and drive them through to resolution Deliver short term fixes rapidly to restore service, while tracking and delivering long term root cause resolutionsMaintain a pragmatic balance between speed of recovery and quality of fix SKILLS & EXPERIENCE Proven experience in a DevOps, infrastructure, or platform engineering role Hands on experience with Kubernetes-deploying, configuring, and operating workloads in a shared or managed cluster environment Experience containerising applications: writing Dockerfiles, managing images, publishing to a registry, and debugging container level issues Strong networking fundamentals: DNS, TLS/SSL certificates, firewall rules, load balancing, VPNs, and service to service connectivity Comfort operating in environments where the architecture is still being defined-able to contribute to the decision, then execute once direction is set Hands on experience with RHEL (or equivalent enterprise Linux)-provisioning, hardening, package management (yum/dnf), systemd services Experience managing cloud infrastructure, ideally in an enterprise private/hybrid cloud environment Experience with infrastructure as code or configuration management tooling (e.g. Terraform, Ansible, Puppet, or similar) Solid scripting ability in Bash and at least one higher level language (Python preferred) Experience with monitoring and observability tooling (e.g. Prometheus, Grafana, Datadog, or similar) Strong incident diagnosis skills-able to work from vague symptoms to root cause using logs, metrics, and reasoning Comfortable working with AI generated or AI assisted codebases: reading, extending, and debugging solutions without a full traditional authorship history Clear written and verbal communication-able to translate infrastructure complexity for non technical stakeholders Experience with AWS or particularly EKS Familiarity with Apple's internal platform tooling: Kube, Shield, Appleconnect, Floodgate, or similar Experience integrating with Snowflake, including managing drivers, credentials, and network access Experience with CI/CD pipelines (GitLab CI, Jenkins, GitHub Actions, or similar) Exposure to security tooling, vulnerability scanning, or compliance frameworks (e.g. CIS Benchmarks) Familiarity with secrets management tooling (Vault, CyberArk, or similar) Experience working in a regulated or enterprise environment with change management processes WAYS OF WORKING You are comfortable with genuine ambiguity-including at the architectural level-and can make progress and contribute to decisions without waiting for everything to be resolved You default to automation: if you do something twice, you script it; if you do it three times, you build a process You adapt quickly: the tools, environments, and solutions you support can change fast, and you treat that as normal rather than exceptional You are pragmatic under pressure: you know when to stop the bleeding first and fix it properly later You are self directed and comfortable owning problems end to end with minimal hand holding You are a willing partner to developers who move fast-you keep up, add guardrails where they matter, and don't become a bottleneck WHAT SUCCESS LOOKS LIKE A new managed container environment is designed, built, and running-with existing VM based workloads migrated onto it in a controlled, sequenced way The standard deployment path (build containerise publish connect) is well established, documented, and easy for the team to use Connectivity from the new environment to Apple internal systems (Snowflake, Appleconnect, Shield, Floodgate, etc.) is reliable, well understood, and correctly secured Teams are unblocked quickly when they need new integrations, access, or capabilities-even when the solutions they are deploying have been built at speed Production issues are resolved rapidly, with lasting fixes following close behind Monitoring catches issues before users do The infrastructure estate-both old and new-is well documented, well understood, and in a known good state
04/07/2026
Full time
We are looking for a skilled and pragmatic DevOps Engineer to own and evolve our infrastructure across the EMEIA region. This is a dual-horizon role: you will keep our existing VM-based systems healthy while leading a greenfield effort to design and build the managed environment that those solutions will migrate onto. A significant proportion of what we build is produced rapidly using AI-assisted, structured development. That means our solutions can move from idea to deployment faster than ever, and our infrastructure needs to keep pace. We need someone who thrives in a fast-moving, ambiguous environment, can absorb change quickly, and treats adaptability as a core part of the job rather than an occasional demand. The new managed environment is most likely to be based on Kube - Apple's internal Kubernetes (EKS) deployment - though the final architecture will be a team decision and remains an option for workloads requiring greater control. You will help inform that decision and then own the build out, regardless of which direction is chosen. You will work closely with data engineers, developers, and analysts, acting as the infrastructure backbone for a team that moves quickly and expects you to move with it. The role also involves working directly with third party vendors who support some of the tools being deployed, and collaborating with teams outside of EMEIA - including WorldWide - to align on standards, share solutions, and resolve cross regional dependencies. KEY RESPONSIBILITIES Lead the design and build out of a new managed container environment to replace existing VM based infrastructure - the most likely candidate is Kube (Apple's internal Kubernetes/EKS cluster), but the final decision will be made collaboratively as a team Contribute meaningfully to the environment selection decision: weigh trade offs between managed solutions (Kube) and more directly controlled alternatives considering maintenance overhead, operational control, and team capability Own the migration of existing VM based workloads onto the new platform, managing sequencing, risk, and continuity of service throughout Establish and maintain the standard workflow for deploying solutions: build locally containerise publish to Kube configure connectivity to Apple internal system dependencies Apple Internal Networking & Connectivity Configure and maintain networking between Kube and Apple's internal systems, including Shield, Snowflake, Appleconnect, Floodgate, and any other platform dependencies the team relies on Own namespace and compute provisioning on the shared Kube cluster, ensuring workloads are appropriately isolated and correctly configured Manage credentials, service accounts, and access controls across the full connectivity chain - from container to downstream service Act as the go to expert on how things connect within Apple's internal network topology Infrastructure Management Own and manage cloud infrastructure across EMEIA using internal cloud tooling (and connected systems including Shield) Manage certificates, firewalls, resource pools, networking, and access controls Ensure infrastructure is appropriately sized, resilient, and cost efficient Maintain accurate documentation of infrastructure topology and configuration Maintain and operate existing virtual machines, primarily on RHEL, while migration to the new environment is in progress Build and maintain standardised, repeatable provisioning processes (e.g. via Ansible, Terraform, or equivalent IaC tooling) Manage package deployment, software repositories, databases, and web servers Own the patching and update lifecycle for managed systems Monitoring & Reliability Implement and maintain monitoring, alerting, and observability across both the existing VM estate and the new container environment Proactively identify risks, bottlenecks, and failure patterns before they impact users Define and track appropriate SLIs/SLOs for critical services Conduct post incident reviews and drive lasting improvements Supporting AI Augmented Development A large proportion of the solutions you will support are built rapidly using structured AI assisted development - you must be comfortable working with codebases and configurations that evolve quickly, may not have deep documentation histories, and may have been substantially generated with AI tooling Provide the infrastructure scaffold that allows AI assisted solutions to move from local development to production reliably and safely Be a pragmatic partner to developers: unblock deployment quickly, catch infrastructure level risks early, and help establish patterns that make rapid iteration safe at scale Actively use AI tools (e.g. Claude, Copilot, or similar) to accelerate your own work: writing scripts, diagnosing issues, generating runbooks, reviewing configurations Diagnosis & Incident Response Take ownership of vague or ambiguous production issues (e.g. "it's running slow", "the server keeps falling over") and drive them through to resolution Deliver short term fixes rapidly to restore service, while tracking and delivering long term root cause resolutionsMaintain a pragmatic balance between speed of recovery and quality of fix SKILLS & EXPERIENCE Proven experience in a DevOps, infrastructure, or platform engineering role Hands on experience with Kubernetes-deploying, configuring, and operating workloads in a shared or managed cluster environment Experience containerising applications: writing Dockerfiles, managing images, publishing to a registry, and debugging container level issues Strong networking fundamentals: DNS, TLS/SSL certificates, firewall rules, load balancing, VPNs, and service to service connectivity Comfort operating in environments where the architecture is still being defined-able to contribute to the decision, then execute once direction is set Hands on experience with RHEL (or equivalent enterprise Linux)-provisioning, hardening, package management (yum/dnf), systemd services Experience managing cloud infrastructure, ideally in an enterprise private/hybrid cloud environment Experience with infrastructure as code or configuration management tooling (e.g. Terraform, Ansible, Puppet, or similar) Solid scripting ability in Bash and at least one higher level language (Python preferred) Experience with monitoring and observability tooling (e.g. Prometheus, Grafana, Datadog, or similar) Strong incident diagnosis skills-able to work from vague symptoms to root cause using logs, metrics, and reasoning Comfortable working with AI generated or AI assisted codebases: reading, extending, and debugging solutions without a full traditional authorship history Clear written and verbal communication-able to translate infrastructure complexity for non technical stakeholders Experience with AWS or particularly EKS Familiarity with Apple's internal platform tooling: Kube, Shield, Appleconnect, Floodgate, or similar Experience integrating with Snowflake, including managing drivers, credentials, and network access Experience with CI/CD pipelines (GitLab CI, Jenkins, GitHub Actions, or similar) Exposure to security tooling, vulnerability scanning, or compliance frameworks (e.g. CIS Benchmarks) Familiarity with secrets management tooling (Vault, CyberArk, or similar) Experience working in a regulated or enterprise environment with change management processes WAYS OF WORKING You are comfortable with genuine ambiguity-including at the architectural level-and can make progress and contribute to decisions without waiting for everything to be resolved You default to automation: if you do something twice, you script it; if you do it three times, you build a process You adapt quickly: the tools, environments, and solutions you support can change fast, and you treat that as normal rather than exceptional You are pragmatic under pressure: you know when to stop the bleeding first and fix it properly later You are self directed and comfortable owning problems end to end with minimal hand holding You are a willing partner to developers who move fast-you keep up, add guardrails where they matter, and don't become a bottleneck WHAT SUCCESS LOOKS LIKE A new managed container environment is designed, built, and running-with existing VM based workloads migrated onto it in a controlled, sequenced way The standard deployment path (build containerise publish connect) is well established, documented, and easy for the team to use Connectivity from the new environment to Apple internal systems (Snowflake, Appleconnect, Shield, Floodgate, etc.) is reliable, well understood, and correctly secured Teams are unblocked quickly when they need new integrations, access, or capabilities-even when the solutions they are deploying have been built at speed Production issues are resolved rapidly, with lasting fixes following close behind Monitoring catches issues before users do The infrastructure estate-both old and new-is well documented, well understood, and in a known good state
Who are we? Zora Ecosystems' mission is to regenerate natural ecosystems responsibly so that the planet and its communities can thrive. We combine proprietary technology and domain expertise with on-the-ground relationships to mobilise landowners, major infrastructure providers, investors, government bodies, and communities around large-scale nature restoration programmes. Zora Ecosystems accelerates nature recovery using data, technology, and rigorous science. Doing the right thing for nature and people is at the heart of our work, and we apply peer-reviewed and novel scientific methods to scope, plan, and support the delivery of on-the-ground regeneration projects. We build systems that enable ecosystem restoration at scale, blending interdisciplinary scientific expertise with geospatial analytics and environmental data science. We combine our technology and domain expertise with on-the-ground relationships to mobilise landowners, investors, government bodies, and communities around large scale nature restoration programmes. We are a venture-backed scale up entering a new phase of growth. After our success working with landowners to deliver projects on the ground, we are now expanding to the demand side of the market. Partnering with large corporates and regulated utilities providers, we will be providing landscape level solutions across a wide range of nature based interventions, targeting a broad scope of outcomes that includes water quality, flood risk, carbon sequestration, biodiversity uplift and many more. WHAT WE STAND FOR NATURE: Nature is at the heart of everything we do. It grounds our decisions, reminds us of the interconnected systems we're part of, and inspires us to design with care, responsibly, and with long term thinking. By staying close to nature, we stay close to what truly matters: impact that creates nature positive outcomes. INNOVATION: Innovation drives our curiosity, courage, and our ambition. We experiment with science and technology to support us in challenging convention. For us, innovation isn't about being novel - it's about creating meaningful progress now for a better tomorrow. TRUST: Trust is the foundation of Zora Ecosystems. We build it through internal engagement with our teams and externally with our clients. People can rely on us to do the right thing, every time. When trust is strong, everything else becomes possible. Trust is the main building block of high performing teams. We are growing our capabilities on landscape approaches to nature restoration and land use, particularly focused on solving grand challenges related to water. We are working with water companies, NGOs and local councils to design and deliver large-scale nature restoration projects that improve outcomes in flooding, drought and water quality. Your mission We're seeking a versatile and outcome-focused researcher with expertise in sciences relating to water supply management, flooding, hydrology, or hydraulic modeling to develop novel and scalable nature based solutions approaches for grand challenges in the water space. In this role you will combine the best in academic research with industry tech to develop novel models and methods that improve water outcomes by restoring ecosystems. Your models and insights will inform real-world landscape regeneration projects, improve biodiversity outcomes, and address the impacts of climate change. Working closely with a multi-disciplinary team of scientists and field practitioners, your work will have a real positive impact on people and the planet. As part of our R&D team, you will work under our Head of Applied Science and our Senior Water Scientist to quantify how nature-based solutions can help mitigate drought and flooding at multiple spatial scales - from landholding to catchment and landscape scales. You will build scalable modeling approaches that can be applied nationally and internationally. In due course, you'll develop approaches to integrating hydrological and hydraulic models with other types of natural process models (such as models relating to soils, peat and biodiversity), and climate model data. You will: Apply remote sensing data, in situ data, and hydrological and hydraulic models to understand water dynamics at the catchment and sub-catchment scales. Co-design landscape interventions to reduce flood risk, mitigate drought, improve water quality, and build new habitats in collaboration with your science team colleagues and our team of field experts. Gather ground truth data to validate desk based model analytics. Develop partnerships and collaborations with academic research groups, water companies, and other businesses in the field of water science. Contribute to improving internal models and research on nature restoration. Apply your geospatial knowledge and skills to solving other landscape-level scientific challenges. Mentor junior science staff and regularly supervise interns. Your profile Requirements: A passion for making a positive impact on the planet and solving grand environmental challenges. A PhD, or equivalent level of experience, in a discipline related to catchment scale hydrology, nature-based solutions, water science, hydraulic modeling, hydrogeology, physics, remote sensing, engineering, or other similar fields. Experience working in Python. Knowledge of processing techniques and manipulation of GIS datasets: proficiency in GIS mapping data and software, and experience in geospatial data analysis. Experience using relevant geospatial data types, such as LiDAR and land cover. A proactive, methodical, and data driven approach to problem-solving. Enthusiasm for working collaboratively with teams comprising different scientific and non-technical backgrounds. The ability to communicate complex technical topics effectively to a non technical audience. Nice to haves: Experience or expertise in hydraulic or hydrological models, hydrogeology or groundwater, soil science, or nature-based solutions relating to these. Experience with AWS or other cloud computing environments, and large geospatial datasets (e.g. using cloud optimised format, manipulating high-resolution spatial data). Experience or expertise in natural capital assessment. Why us? For more information on our ways of working, culture, and mission, please refer to:
01/07/2026
Full time
Who are we? Zora Ecosystems' mission is to regenerate natural ecosystems responsibly so that the planet and its communities can thrive. We combine proprietary technology and domain expertise with on-the-ground relationships to mobilise landowners, major infrastructure providers, investors, government bodies, and communities around large-scale nature restoration programmes. Zora Ecosystems accelerates nature recovery using data, technology, and rigorous science. Doing the right thing for nature and people is at the heart of our work, and we apply peer-reviewed and novel scientific methods to scope, plan, and support the delivery of on-the-ground regeneration projects. We build systems that enable ecosystem restoration at scale, blending interdisciplinary scientific expertise with geospatial analytics and environmental data science. We combine our technology and domain expertise with on-the-ground relationships to mobilise landowners, investors, government bodies, and communities around large scale nature restoration programmes. We are a venture-backed scale up entering a new phase of growth. After our success working with landowners to deliver projects on the ground, we are now expanding to the demand side of the market. Partnering with large corporates and regulated utilities providers, we will be providing landscape level solutions across a wide range of nature based interventions, targeting a broad scope of outcomes that includes water quality, flood risk, carbon sequestration, biodiversity uplift and many more. WHAT WE STAND FOR NATURE: Nature is at the heart of everything we do. It grounds our decisions, reminds us of the interconnected systems we're part of, and inspires us to design with care, responsibly, and with long term thinking. By staying close to nature, we stay close to what truly matters: impact that creates nature positive outcomes. INNOVATION: Innovation drives our curiosity, courage, and our ambition. We experiment with science and technology to support us in challenging convention. For us, innovation isn't about being novel - it's about creating meaningful progress now for a better tomorrow. TRUST: Trust is the foundation of Zora Ecosystems. We build it through internal engagement with our teams and externally with our clients. People can rely on us to do the right thing, every time. When trust is strong, everything else becomes possible. Trust is the main building block of high performing teams. We are growing our capabilities on landscape approaches to nature restoration and land use, particularly focused on solving grand challenges related to water. We are working with water companies, NGOs and local councils to design and deliver large-scale nature restoration projects that improve outcomes in flooding, drought and water quality. Your mission We're seeking a versatile and outcome-focused researcher with expertise in sciences relating to water supply management, flooding, hydrology, or hydraulic modeling to develop novel and scalable nature based solutions approaches for grand challenges in the water space. In this role you will combine the best in academic research with industry tech to develop novel models and methods that improve water outcomes by restoring ecosystems. Your models and insights will inform real-world landscape regeneration projects, improve biodiversity outcomes, and address the impacts of climate change. Working closely with a multi-disciplinary team of scientists and field practitioners, your work will have a real positive impact on people and the planet. As part of our R&D team, you will work under our Head of Applied Science and our Senior Water Scientist to quantify how nature-based solutions can help mitigate drought and flooding at multiple spatial scales - from landholding to catchment and landscape scales. You will build scalable modeling approaches that can be applied nationally and internationally. In due course, you'll develop approaches to integrating hydrological and hydraulic models with other types of natural process models (such as models relating to soils, peat and biodiversity), and climate model data. You will: Apply remote sensing data, in situ data, and hydrological and hydraulic models to understand water dynamics at the catchment and sub-catchment scales. Co-design landscape interventions to reduce flood risk, mitigate drought, improve water quality, and build new habitats in collaboration with your science team colleagues and our team of field experts. Gather ground truth data to validate desk based model analytics. Develop partnerships and collaborations with academic research groups, water companies, and other businesses in the field of water science. Contribute to improving internal models and research on nature restoration. Apply your geospatial knowledge and skills to solving other landscape-level scientific challenges. Mentor junior science staff and regularly supervise interns. Your profile Requirements: A passion for making a positive impact on the planet and solving grand environmental challenges. A PhD, or equivalent level of experience, in a discipline related to catchment scale hydrology, nature-based solutions, water science, hydraulic modeling, hydrogeology, physics, remote sensing, engineering, or other similar fields. Experience working in Python. Knowledge of processing techniques and manipulation of GIS datasets: proficiency in GIS mapping data and software, and experience in geospatial data analysis. Experience using relevant geospatial data types, such as LiDAR and land cover. A proactive, methodical, and data driven approach to problem-solving. Enthusiasm for working collaboratively with teams comprising different scientific and non-technical backgrounds. The ability to communicate complex technical topics effectively to a non technical audience. Nice to haves: Experience or expertise in hydraulic or hydrological models, hydrogeology or groundwater, soil science, or nature-based solutions relating to these. Experience with AWS or other cloud computing environments, and large geospatial datasets (e.g. using cloud optimised format, manipulating high-resolution spatial data). Experience or expertise in natural capital assessment. Why us? For more information on our ways of working, culture, and mission, please refer to:
Who are we? Zora Ecosystems' mission is to regenerate natural ecosystems responsibly so that the planet and its communities can thrive. We combine proprietary technology and domain expertise with on-the-ground relationships to mobilise landowners, major infrastructure providers, investors, government bodies, and communities around large-scale nature restoration programmes. Zora Ecosystems accelerates nature recovery using data, technology, and rigorous science. Doing the right thing for nature and people is at the heart of our work, and we apply peer-reviewed and novel scientific methods to scope, plan, and support the delivery of on-the-ground regeneration projects. We build systems that enable ecosystem restoration at scale, blending interdisciplinary scientific expertise with geospatial analytics and environmental data science. We combine our technology and domain expertise with on-the-ground relationships to mobilise landowners, investors, government bodies, and communities around large scale nature restoration programmes. We are a venture-backed scale up entering a new phase of growth. After our success working with landowners to deliver projects on the ground, we are now expanding to the demand side of the market. Partnering with large corporates and regulated utilities providers, we will be providing landscape level solutions across a wide range of nature based interventions, targeting a broad scope of outcomes that includes water quality, flood risk, carbon sequestration, biodiversity uplift and many more. WHAT WE STAND FOR NATURE: Nature is at the heart of everything we do. It grounds our decisions, reminds us of the interconnected systems we're part of, and inspires us to design with care, responsibly, and with long term thinking. By staying close to nature, we stay close to what truly matters: impact that creates nature positive outcomes. INNOVATION: Innovation drives our curiosity, courage, and our ambition. We experiment with science and technology to support us in challenging convention. For us, innovation isn't about being novel - it's about creating meaningful progress now for a better tomorrow. TRUST: Trust is the foundation of Zora Ecosystems. We build it through internal engagement with our teams and externally with our clients. People can rely on us to do the right thing, every time. When trust is strong, everything else becomes possible. Trust is the main building block of high performing teams. We are growing our capabilities on landscape approaches to nature restoration and land use, particularly focused on solving grand challenges related to water. We are working with water companies, NGOs and local councils to design and deliver large-scale nature restoration projects that improve outcomes in flooding, drought and water quality. Your mission We're seeking a versatile and outcome-focused researcher with expertise in sciences relating to water supply management, flooding, hydrology, or hydraulic modeling to develop novel and scalable nature based solutions approaches for grand challenges in the water space. In this role you will combine the best in academic research with industry tech to develop novel models and methods that improve water outcomes by restoring ecosystems. Your models and insights will inform real-world landscape regeneration projects, improve biodiversity outcomes, and address the impacts of climate change. Working closely with a multi-disciplinary team of scientists and field practitioners, your work will have a real positive impact on people and the planet. As part of our R&D team, you will work under our Head of Applied Science and our Senior Water Scientist to quantify how nature-based solutions can help mitigate drought and flooding at multiple spatial scales - from landholding to catchment and landscape scales. You will build scalable modeling approaches that can be applied nationally and internationally. In due course, you'll develop approaches to integrating hydrological and hydraulic models with other types of natural process models (such as models relating to soils, peat and biodiversity), and climate model data. You will: Apply remote sensing data, in situ data, and hydrological and hydraulic models to understand water dynamics at the catchment and sub-catchment scales. Co-design landscape interventions to reduce flood risk, mitigate drought, improve water quality, and build new habitats in collaboration with your science team colleagues and our team of field experts. Gather ground truth data to validate desk based model analytics. Develop partnerships and collaborations with academic research groups, water companies, and other businesses in the field of water science. Contribute to improving internal models and research on nature restoration. Apply your geospatial knowledge and skills to solving other landscape-level scientific challenges. Mentor junior science staff and regularly supervise interns. Your profile Requirements: A passion for making a positive impact on the planet and solving grand environmental challenges. A PhD, or equivalent level of experience, in a discipline related to catchment scale hydrology, nature-based solutions, water science, hydraulic modeling, hydrogeology, physics, remote sensing, engineering, or other similar fields. Experience working in Python. Knowledge of processing techniques and manipulation of GIS datasets: proficiency in GIS mapping data and software, and experience in geospatial data analysis. Experience using relevant geospatial data types, such as LiDAR and land cover. A proactive, methodical, and data driven approach to problem-solving. Enthusiasm for working collaboratively with teams comprising different scientific and non-technical backgrounds. The ability to communicate complex technical topics effectively to a non technical audience. Nice to haves: Experience or expertise in hydraulic or hydrological models, hydrogeology or groundwater, soil science, or nature-based solutions relating to these. Experience with AWS or other cloud computing environments, and large geospatial datasets (e.g. using cloud optimised format, manipulating high-resolution spatial data). Experience or expertise in natural capital assessment. Why us? For more information on our ways of working, culture, and mission, please refer to:
01/07/2026
Full time
Who are we? Zora Ecosystems' mission is to regenerate natural ecosystems responsibly so that the planet and its communities can thrive. We combine proprietary technology and domain expertise with on-the-ground relationships to mobilise landowners, major infrastructure providers, investors, government bodies, and communities around large-scale nature restoration programmes. Zora Ecosystems accelerates nature recovery using data, technology, and rigorous science. Doing the right thing for nature and people is at the heart of our work, and we apply peer-reviewed and novel scientific methods to scope, plan, and support the delivery of on-the-ground regeneration projects. We build systems that enable ecosystem restoration at scale, blending interdisciplinary scientific expertise with geospatial analytics and environmental data science. We combine our technology and domain expertise with on-the-ground relationships to mobilise landowners, investors, government bodies, and communities around large scale nature restoration programmes. We are a venture-backed scale up entering a new phase of growth. After our success working with landowners to deliver projects on the ground, we are now expanding to the demand side of the market. Partnering with large corporates and regulated utilities providers, we will be providing landscape level solutions across a wide range of nature based interventions, targeting a broad scope of outcomes that includes water quality, flood risk, carbon sequestration, biodiversity uplift and many more. WHAT WE STAND FOR NATURE: Nature is at the heart of everything we do. It grounds our decisions, reminds us of the interconnected systems we're part of, and inspires us to design with care, responsibly, and with long term thinking. By staying close to nature, we stay close to what truly matters: impact that creates nature positive outcomes. INNOVATION: Innovation drives our curiosity, courage, and our ambition. We experiment with science and technology to support us in challenging convention. For us, innovation isn't about being novel - it's about creating meaningful progress now for a better tomorrow. TRUST: Trust is the foundation of Zora Ecosystems. We build it through internal engagement with our teams and externally with our clients. People can rely on us to do the right thing, every time. When trust is strong, everything else becomes possible. Trust is the main building block of high performing teams. We are growing our capabilities on landscape approaches to nature restoration and land use, particularly focused on solving grand challenges related to water. We are working with water companies, NGOs and local councils to design and deliver large-scale nature restoration projects that improve outcomes in flooding, drought and water quality. Your mission We're seeking a versatile and outcome-focused researcher with expertise in sciences relating to water supply management, flooding, hydrology, or hydraulic modeling to develop novel and scalable nature based solutions approaches for grand challenges in the water space. In this role you will combine the best in academic research with industry tech to develop novel models and methods that improve water outcomes by restoring ecosystems. Your models and insights will inform real-world landscape regeneration projects, improve biodiversity outcomes, and address the impacts of climate change. Working closely with a multi-disciplinary team of scientists and field practitioners, your work will have a real positive impact on people and the planet. As part of our R&D team, you will work under our Head of Applied Science and our Senior Water Scientist to quantify how nature-based solutions can help mitigate drought and flooding at multiple spatial scales - from landholding to catchment and landscape scales. You will build scalable modeling approaches that can be applied nationally and internationally. In due course, you'll develop approaches to integrating hydrological and hydraulic models with other types of natural process models (such as models relating to soils, peat and biodiversity), and climate model data. You will: Apply remote sensing data, in situ data, and hydrological and hydraulic models to understand water dynamics at the catchment and sub-catchment scales. Co-design landscape interventions to reduce flood risk, mitigate drought, improve water quality, and build new habitats in collaboration with your science team colleagues and our team of field experts. Gather ground truth data to validate desk based model analytics. Develop partnerships and collaborations with academic research groups, water companies, and other businesses in the field of water science. Contribute to improving internal models and research on nature restoration. Apply your geospatial knowledge and skills to solving other landscape-level scientific challenges. Mentor junior science staff and regularly supervise interns. Your profile Requirements: A passion for making a positive impact on the planet and solving grand environmental challenges. A PhD, or equivalent level of experience, in a discipline related to catchment scale hydrology, nature-based solutions, water science, hydraulic modeling, hydrogeology, physics, remote sensing, engineering, or other similar fields. Experience working in Python. Knowledge of processing techniques and manipulation of GIS datasets: proficiency in GIS mapping data and software, and experience in geospatial data analysis. Experience using relevant geospatial data types, such as LiDAR and land cover. A proactive, methodical, and data driven approach to problem-solving. Enthusiasm for working collaboratively with teams comprising different scientific and non-technical backgrounds. The ability to communicate complex technical topics effectively to a non technical audience. Nice to haves: Experience or expertise in hydraulic or hydrological models, hydrogeology or groundwater, soil science, or nature-based solutions relating to these. Experience with AWS or other cloud computing environments, and large geospatial datasets (e.g. using cloud optimised format, manipulating high-resolution spatial data). Experience or expertise in natural capital assessment. Why us? For more information on our ways of working, culture, and mission, please refer to: