Role: AWS Data Engineer Experience: 10years Location: London Work mode: Hybrid Job Discerption: We are building the next-generation data platform at FTSE Russell — and we want you to shape it with us. Your role will involve: • Designing and developing scalable, testable data pipelines using Python and Apache Spark • Orchestrating data workflows with AWS tools like Glue, EMR Serverless, Lambda, and S3 • Applying modern software engineering practices: version control, CI/CD, modular design, and automated testing • Contributing to the development of a lakehouse architecture using Apache Iceberg • Collaborating with business teams to translate requirements into data-driven solutions • Building observability into data flows and implementing basic quality checks • Participating in code reviews, pair programming, and architecture discussions • Continuously learning about the financial indices domain and sharing insights with the team WHAT YOU'LL BRING: Writes clean, maintainable Python code (ideally with type hints, linters, and tests like pytest) Understands data engineering basics: batch processing, schema evolution, and building ETL pipelines Has experience with or is eager to learn Apache Spark for large-scale data processing Is familiar with the AWS data stack (e.g. S3, Glue, Lambda, EMR) Enjoys learning the business context and working closely with stakeholders • Works well in Agile teams and values collaboration over solo heroics Nice-to-haves: It’s great (but not required) if you also bring: Experience with Apache Iceberg or similar table formats Familiarity with CI/CD tools like GitLab CI, Jenkins, or GitHub Actions Exposure to data quality frameworks like Great Expectations or Deequ Curiosity about financial markets, index data, or investment analytics