AWS Data Engineer

Role – AWS Data Engineer Location : London, UK 12 Months FTC Work Mode : Hybrid Need Expert in Python Pyspark, AWS, Cloud, AWS Services, AWS Components • 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