ROLE SUMMARY
Ready to build scalable data systems with real-world impact? Join us at FTSE Russell! We’re establishing a team of engineers passionate about data, software craftsmanship, and substantial impact. As a Lead Software Data Engineer, you’ll help power the indices trusted by financial institutions worldwide. You’ll work in a modern AWS environment, build robust pipelines, and collaborate closely with product and business teams to deliver reliable, high-quality data solutions. We care about code quality, ownership, and helping each other grow. If you’re excited about building systems that matter, we’d love to meet you!
WHAT YOU’LL BE DOING
- 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, testable, extensible 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)
- Strong experience in relational databases (e.g. Aurora PostgreSQL)
- Enjoys learning the business context and working closely with stakeholders
- Works well in Agile teams and values collaboration over solo heroics
NICE TO HAVES
- 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
- Experience with other data platforms like Databricks, etc.
- Curiosity about financial markets, index data, or investment analytics
Equal Opportunities Statement
We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone’s race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.
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