Sagacity

Platform Architecture & Engineering responsibilities: Design and implement scalable Databricks Lakehouse platforms on AWS and/or Azure aligned to client requirements Architect end-to-end data platforms including ingestion, storage (Delta Lake), processing, and consumption layers Build and configure cloud infrastructure using infrastructure-as-code (e.g. Terraform & Declarative Automation Bundles(DAB's Establish secure, compliant environments including networking (VNet/VPC, Private Link), identity (IAM/Entra ID), data governance (Unity Catalog), and access controls Define environment strategies (dev/test/prod), CI/CD pipelines, and release processes for Databricks deployments Implement monitoring, logging, cost optimisation, and performance tuning across the platform Design and implement data pipelines using Delta Live Tables, Auto Loader, and Databricks Workflows for both batch and streaming workloads Client Delivery & Enablement responsibilities: Work directly with clients to translate business and technical requirements into scalable platform designs Lead technical workshops, architecture sessions, and whiteboarding engagements with client stakeholders Support rapid prototyping and proof-of-concept builds within Databricks to demonstrate platform capabilities and accelerate client adoption Provide best practice guidance on Lakehouse architecture, data modelling, workload optimisation, and cost management Produce high-quality technical documentation including architecture diagrams, architecture decision records (ADRs), runbooks, and deployment guides Enable client teams through structured knowledge transfer, training, and platform handover Collaborate with data engineers, data scientists, and product teams to ensure successful delivery outcomes Governance & Security: Implement Unity Catalog for centralised data governance, including access control (RBAC/ABAC), data lineage, audit logging, and compliance enforcement Apply security best practices across platform design: network isolation, secret management, encryption at rest and in transit, and identity federation Ensure platform designs meet client regulatory and compliance requirements (e.g. GDPR, ISO 27001, sector-specific standards) What success looks like in the role: Delivery of robust, secure, and scalable Databricks platforms that meet client performance and cost expectations Clear, well-architected solutions that balance flexibility, governance, and operational efficiency Strong client relationships built on trust, technical credibility, and effective communication Accelerated client adoption of the Lakehouse platform through well-designed enablement and documentation Reduced deployment time through reusable infrastructure patterns and automation Proactive identification of risks, trade-offs, and optimisation opportunities across platform design and delivery Contribution to the organisation's growing body of reusable platform accelerators, reference architectures, and internal knowledge Competencies and Behaviours: 3+ years experience in data platform engineering, cloud engineering, or similar roles Strong hands-on experience with Databricks, including Apache Spark, Delta Lake, Workflows Proven experience designing and deploying data platforms on AWS and/or Azure (e.g. ADLS, S3, VNet/VPC, IAM) Experience with infrastructure-as-code tools (e.g. Terraform preferred) and CI/CD pipelines (e.g. Azure DevOps, GitHub Actions) Solid understanding of data architecture concepts including Lakehouse medallion architecture and dimensional modelling Familiarity with security and governance frameworks (e.g. RBAC, ABAC, data masking, audit, compliance standards) Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders Comfortable working in a client-facing consultancy environment with multiple concurrent engagements Proactive, self-driven, and able to take ownership of end-to-end platform delivery Willingness to travel within the UK as required Right to work in the UK