Data engineer

Royal Mail is transforming how it uses data and technology to improve efficiency, support better decision-making and create value for our customers and colleagues. We're looking for a Senior Data Engineer to play a pivotal role in delivering our data strategy. Working closely with Data Analytics, Data Science, Machine Learning Engineering and Technology teams, you'll help design and build scalable data products that solve real business challenges across one of the UK's largest and most complex organisations.

• Leading the design, development and delivery of scalable data pipelines and products that create measurable business value.
• Designing, optimising and monitoring our cloud data platform, with a particular focus on Google Cloud Platform.
• Establishing simple, standardised and innovative approaches to ingesting, processing, storing and analysing data.
• Leading teams responsible for sourcing, transforming and delivering data that supports frontline operations and strategic decision-making.
• Owning the technical lifecycle of data products, from initial concept and design through to delivery, incident management and BAU support.
• Working with Data Scientists and Machine Learning Engineers to deploy machine learning and AI use cases into production.
• Building automation across CI/CD pipelines, testing, infrastructure management, release processes and configuration.
• Overseeing technical priorities, resource allocation and delivery estimates across the data product portfolio.
• Working with Product Owners, Delivery Managers and business stakeholders to resolve technical challenges and deliver agreed outcomes.
• Supporting pilot and innovation activity across the organisation.
• Ensuring data products are documented effectively and handed over smoothly to internal teams and suppliers.
• Coaching and mentoring Data Engineers while promoting engineering best practice and reducing technical debt.

You’ll be an experienced Data Engineer with a strong track record of building and delivering production-ready data solutions in complex environments. Significant Data Engineering experience, with evidence of delivering solutions that have created measurable business value. Strong experience using Python or Scala. Hands-on knowledge of Big Data and streaming technologies such as Spark and Kafka. Experience designing data models, ETL and ELT pipelines, data warehouses and data lakes.

Practical experience with Google Cloud tools such as Big Query, Dataflow, Dataproc, Pub/Sub, Composer and Dataplex, or comparable services within Azure or AWS. Strong knowledge of SQL, databases, metadata management and data governance. Experience working with CI/CD toolsets, Kubernetes, release management, automated testing and cloud deployments. Knowledge of test-driven or behaviour-driven development practices, including TDD and BDD. Experience using tools such as Jira and Confluence within Agile delivery environments.

An understanding of MLOps practices and how data engineering supports scalable machine learning and AI deployment. Experience managing distributed applications across cloud environments, ideally including Google Cloud Platform and Microsoft Azure. Strong communication and stakeholder management skills, with the ability to explain complex technical topics clearly. A structured and analytical approach to solving problems, with the confidence to challenge constructively.

Experience coaching or mentoring engineers and improving technical standards across a team. Будет плюсом: A relevant degree or recognised Cloud Engineering certifications, ideally relating to Google Cloud, would also be valuable.

• Competitive salary
• Car allowance
• Healthcare
• Up to 18% annual bonus potential
• 25 days annual leave plus bank…