Senior Data Engineer d/f/m

Senior Data Engineer d/f/m

Location(s):

Swindon, Wiltshire, GB, SN5 6PB London, City of London, GB, EC2R 8HP Essen, NW, DE, 45141

RWE Supply & Trading GmbH

To start as soon as possible, full time / part time, permanent

Functional area: IT / Digital

Remuneration: tariff/non-tariff

Department Insights

Its an exciting time to join us! The RWEST Data Platform Team is looking for a Senior Data Engineer to help shape the future of data, AI and analytics across our organisation, using modern cloud, Databricks and AI technologies to deliver scalable, trusted and business-critical data solutions.

Our Lead in Data (LiD) platform is the primary data analytics platform within the group and continues to transform how data is discovered, shared, onboarded and governed. By combining cloud-native data engineering with Databricks, advanced analytics and emerging AI capabilities, we are enabling faster access to high-quality market data and creating a stronger foundation for intelligent decision-making across trading, analysis and support functions.

We are looking for a curious, motivated technology enthusiast to join us as a Senior Data Engineer. You will work closely with business stakeholders, Data engineers, DevOps engineers and internal squads to define the future direction of our platform, explore innovative AI-enabled use cases, and help build robust data products that deliver measurable value.

If you are passionate about data formats, Databricks, engineering and the practical application of AI technologies, then apply now or contact me for an informal chat!

Your future responsibilities

Take ownership of the technical design and evolution of our data analytics platform, integrating new use cases and data sources while ensuring strong performance, scalability, robustness, availability, maintainability and appropriate data latency.

Explore and apply AI-enabled engineering tools and technologies, including code assistants, intelligent automation, data quality accelerators and emerging AI use cases that improve developer productivity, platform operations and user outcomes.

Design and implement high-quality data pipelines and data products using strong SQL skills, modern data engineering patterns, cloud-native services, Spark and Databricks capabilities including notebooks, jobs, workflows and Delta Lake.

Work confidently with common data formats and storage patterns such as Parquet, Delta, CSV, JSON and structured/semi-structured datasets, ensuring data is modelled, curated, documented and made available in a reliable and reusable way.

Act as the interface between key business stakeholders, Product Owners, Data Engineers and DevOps Engineers, translating business requirements into clear technical backlog items, architecture decisions and delivery roadmaps.

Shape and influence the technical delivery backlog with innovation ideas, platform enhancements, automation opportunities and technical requirements gathered from users, engineers, vendors and operational insights.

Contribute as a senior technical problem solver in a multidisciplinary team, creating pragmatic solutions for complex data platform requirements with a strong focus on engineering quality, observability, security and operational excellence.

Keep up to date with trends in data analytics, Lakehouse architecture, Databricks, AI/ML tooling, data governance and modern engineering practices, identifying where new technologies can solve real business and platform problems.

Engage with platform vendors prioritising fixes, understanding product roadmaps, assessing technical and commercial impact, and managing usage, billing and adoption considerations.