Data Engineer

  • Service Care Solutions Ltd
  • Long Stratton, Norfolk
  • 23/06/2026
Full time Information Technology Telecommunications

Job Description

Job Title: Data Engineer

Location: Long Stratton, Norfolk NR15 (Hybrid - Fortnightly Office Attendance)

Contract: Permanent

Hours: Full time (37 hours per week)

Salary: £63,000 per annum

About the Role

This is an opportunity to join a growing Data & Analytics team and take ownership of a modern Azure data platform. You'll be responsible for building and maintaining data pipelines, developing data warehouse solutions, and supporting the organisation's move towards Microsoft Fabric.

Responsibilities
  • Design, build and maintain a scalable Azure-based data warehouse to support reporting, analytics and business intelligence requirements.
  • Develop and maintain robust ETL/ELT processes, data integration frameworks and transformation pipelines using Azure Data Factory, Azure Synapse and Microsoft Fabric technologies.
  • Support the implementation, optimisation and ongoing development of Microsoft Fabric, including Lakehouse, Warehouse, Data Engineering and Data Pipeline capabilities.
  • Design and maintain efficient data models, ensuring data structures support both operational and analytical reporting requirements.
  • Build reusable, parameterised and scalable data pipelines that integrate data from multiple internal and external sources.
  • Monitor and maintain data pipelines, implementing automated alerting, logging and performance monitoring to ensure platform reliability.
  • Work closely with BI Analysts and business stakeholders to understand data requirements and deliver scalable engineering solutions.
  • Implement data quality controls, validation rules and automated testing processes to improve data accuracy and consistency.
  • Support the development and maintenance of data governance standards, metadata management and technical documentation.
  • Ensure compliance with GDPR and data security requirements across all data solutions.
  • Contribute to cloud infrastructure decisions, platform optimisation and storage strategies to maximise performance and cost efficiency.
  • Utilise Azure DevOps and Git to support CI/CD processes, version control and automated deployments.
  • Provide technical guidance to colleagues and promote best practice across data engineering and platform development.
  • Drive continuous improvement initiatives and identify opportunities to automate manual processes and enhance data accessibility across the organisation.
Requirements
  • Proven experience working as a Data Engineer, Azure Data Engineer, ETL Developer or similar role.
  • Advanced SQL skills, including writing, optimising and troubleshooting complex queries, stored procedures and data transformations.
  • Strong experience designing and building ETL/ELT pipelines using Azure Data Factory, Azure Synapse, Databricks, Airflow or similar technologies.
  • Hands on experience working with Azure cloud data platforms, including Data Lake, Synapse Analytics and related services.
  • Strong understanding of data warehousing concepts and data modelling methodologies, including star schema and dimensional modelling techniques.
  • Experience designing scalable data architectures and integrating data from multiple systems and applications.
  • Knowledge of CI/CD processes, source control and deployment automation using Azure DevOps, Git or similar tools.
  • Experience implementing data quality, validation and monitoring processes.
  • Strong understanding of data governance, security principles and GDPR requirements.
  • Excellent problem solving skills with the ability to identify root causes and implement long term solutions.
  • Strong communication skills with the ability to engage effectively with both technical and non technical stakeholders.
  • Ability to manage multiple priorities and deliver high quality solutions within agreed timescales.
Desirable
  • Experience working with Microsoft Fabric, including Lakehouse, Warehouse and Data Pipelines.
  • Knowledge of Python and/or Scala for data engineering and automation.
  • Experience with Docker, Kubernetes or other containerisation technologies.
  • Exposure to machine learning pipelines or MLOps frameworks.
  • Experience with data quality frameworks such as Great Expectations.
  • Knowledge of Dynamics365 or housing management systems.
  • Microsoft Azure, SQL or Data Engineering certifications.