Data Engineer

Data Engineer (6-Month FTC - salary advertised is yearly and will then be pro-rated to 6 month equivalent) London x3~ days a week (some weeks x2 days) About the Company We're working with a leading UK-based transport and technology business that’s at the forefront of digital transformation in the travel sector. With a strong focus on customer innovation and data-led services, they’re investing heavily in AI and machine learning to shape the future of how journeys are personalised, optimised, and experienced. Their culture supports forward-thinking, autonomy, and continuous improvement, making it a great place for tech professionals who love solving real-world challenges at scale. About the Role This is an exciting opportunity for a passionate Data Engineer to join a growing, high-impact machine learning team. You’ll be instrumental in building and optimising the data pipelines that power AI solutions across the organisation—solutions that directly improve both customer experiences and internal operational efficiencies. In this role, you’ll work closely with data scientists and product teams to enable the successful development and deployment of machine learning models. From sourcing and managing large-scale datasets, to mentoring colleagues on data best practices, you’ll play a critical role in the full lifecycle of AI product delivery. Responsibilities Creating robust, scalable data pipelines to support the delivery and performance of machine learning products. Extracting and integrating data from multiple sources—including across internal teams and distributed systems—to support advanced analytics. Designing and maintaining relational and non-relational databases to ensure data is optimised for modelling and analysis. Supporting data scientists with clean, structured datasets tailored for model training and validation. Overseeing data QA processes and metadata tracking for deployed machine learning models. Leading the creation and upkeep of data documentation, including data dictionaries and version tracking protocols. Contributing to the team’s knowledge sharing and mentoring culture by promoting best practices across data engineering processes. Playing a key role in shaping the strategy for how data supports ML development within the wider organisation. Requirements Proven experience handling and processing large volumes of raw data from multiple sources, with a strong focus on data cleansing and preparation. Solid understanding of data modelling and warehousing, including the design and maintenance of scalable ETL solutions. Strong command of SQL and Python, particularly for working with complex datasets and building data pipelines. Experience working in cloud-based environments, with exposure to tools such as AWS Redshift, Glue, S3, Athena, or Google BigQuery. Hands-on experience managing data versioning, metadata, and documentation for large-scale projects. A track record of collaborating with cross-functional teams, particularly in data science and product development contexts. Familiarity with Agile development practices and a disciplined approach to version control, testing, and deployment. Excellent communication skills—comfortable translating complex technical concepts for different audiences. Experience working within a Unix-based environment. Background in building distributed data systems or pipelines at scale. Knowledge of Scala, Spark, or experience supporting machine learning pipelines is a bonus. If this role interests you and you would like to find out more (or find out about other roles), please apply here or contact us via niall.wharton@Xcede.com (feel free to include a CV for review).

Location: London, GB

Posted Date: 5/13/2025