AWS Data Engineer

Need 10+ years of experience

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:

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Writes clean, maintainable Python code (ideally with type hints, linters, and tests like pytest)

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Understands data engineering basics: batch processing, schema evolution, and building ETL pipelines

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Has experience with or is eager to learn Apache Spark for large-scale data processing

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Is familiar with the AWS data stack (e.g. S3, Glue, Lambda, EMR)

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Enjoys learning the business context and working closely with stakeholders
• Works well in Agile teams and values collaboration over solo heroics

Nice-to-haves:

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It's great (but not required) if you also bring:

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Experience with Apache Iceberg or similar table formats

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Familiarity with CI/CD tools like GitLab CI, Jenkins, or GitHub Actions

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Exposure to data quality frameworks like Great Expectations or Deequ

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Curiosity about financial markets, index data, or investment analytics