Whitehall Resources currently require an experienced Data Engineer to work with a key client based in London
Please note this role falls INSIDE IR35
What you’ll do
- Engineer production grade data pipelines on AWS (EMR, S3, Lambda), using PySpark/Python and SQL, with a focus on performance, resilience, testing, and observability.
- Migrate and modernise legacy workloads (e.g., ETL jobs and reporting feeds) onto cloud native services, creating reusable components and shared frameworks.
- Support reporting & MI use cases, including transformations and data models that feed downstream tools (e.g., Power BI).
- Own CI/CD and version control practices (e.g., Git/GitLab), review code, and enforce engineering standards.
- Coach and mentor engineers, provide technical guidance/code reviews, and contribute to architectural decisions across squads.
- Work in Agile delivery, collaborating across product, data, and platform teams using Jira/Confluence; translate requirements into robust engineering tasks.
- Embed security and compliance by design, aligning with BPSS/SC constraints and department data handling policies.
Essential skills & experience
- Hands on expertise in AWS & Spark: Amazon EMR, S3, Lambda; strong PySpark/Python and SQL for large scale batch processing.
- Data engineering at scale in government or similarly complex domains, including performance tuning and data quality management.
- CI/CD & DevOps: pipelines and IaC (e.g., Terraform), automated testing, and release governance.
- Version control & collaboration: Git/GitLab, code review, branching strategies, and trunk/PR workflows.
- APIs & integration: building/consuming data services to move and expose data safely and reliably.
- Agile ways of working with Jira/Confluence; clear stakeholder communication and concise technical documentation.
- Security clearance: BPSS (minimum) and SC cleared or SC clearable for UK government work.
- Data warehousing & modeling (e.g., Redshift; dimensional modeling; dbt).
- Basic Power BI familiarity to partner with BI developers and validate end to end data flows.
- AWS ecosystem depth (Athena, Redshift, EC2, CloudWatch, IAM) and event driven patterns.
Certifications (nice to have)
- AWS Certified Cloud Practitioner (or higher), Azure AI Fundamentals (awareness of ML/AI services).
- Autonomy: Works under general direction; plans own work; designs and implements PySpark jobs on EMR, modernising legacy code with minimal supervision.
- Influence: Shapes standards through code reviews and mentoring; influences delivery outcomes across teams.
- Complexity: Handles substantial, multifaceted engineering tasks (e.g., migration to new MI platform; data quality resolution; estimating effort).
- Business skills: Communicates effectively with stakeholders; aligns data products to reporting/decision making needs; contributes to Agile ceremonies.
