Data Engineer

As a Senior Data Engineer at Royal Mail, you will drive the design and delivery of scalable data pipelines and products that enable data-driven decisions across a large national organisation. You will work closely with analytics, science and technology teams to shape data platforms, optimise cloud pipelines and deploy ML use cases. The role offers visibility to influence engineering standards and grow the data engineering capability. You’ll tackle real business challenges, building value across frontline operations and strategic decision-making. This is an opportunity to lead technical delivery in a fast-evolving data, cloud and AI environment.

• Car allowance
• Healthcare
• Up to 18% annual bonus
• 25 days annual leave + bank holidays
• Pension with CDC and 12%+ contributions
• Family friendly support

• Lead design, development and delivery of scalable data pipelines and products with measurable business value
• Design, optimise and monitor the cloud data platform, focusing on Google Cloud Platform
• Standardise ingestion, processing, storage and analysis of data
• Lead teams delivering data supporting frontline operations and strategic decisions
• Own the data product lifecycle from concept to delivery, incident management and BAU support
• Collaborate with Data Scientists and ML Engineers to deploy ML/AI use cases
• Automate CI/CD, testing, infrastructure management, release processes and configurations
• Prioritise technical work, allocate resources and provide delivery estimates across data products
• Coordinate with Product Owners, Delivery Managers and stakeholders to resolve technical challenges
• Support pilot/innovation activities and ensure proper documentation and handover

• Extensive Data Engineering experience delivering production-ready solutions
• Proficiency in Python or Scala
• Hands-on Big Data and streaming tech (Spark, Kafka)
• Experience with ETL/ELT, data warehouses and data lakes
• Proficient with Google Cloud tools (BigQuery, Dataflow, Dataproc, Pub/Sub, Composer, Dataplex) or Azure/AWS equivalents
• Strong SQL, databases, metadata management and data governance
• Experience with CI/CD, Kubernetes, release management, testing and cloud deployments
• Knowledge of TDD/BDD
• Familiarity with Jira and Confluence in Agile environments
• Understanding of MLOps and scalable ML/AI deployment
• Experience managing distributed cloud applications, ideally GCP and Azure
• Strong communication and stakeholder management
• Structured, analytical problem-solver with ability to challenge constructively
• Experience coaching/mentoring engineers and improving technical standards
• Relevant degree or recognized Cloud Engineering certifications (beneficial)

• strong communication
• stakeholder management
• mentoring and coaching
• Python
• Scala
• Spark