Senior Data Engineer (SQL)

We are seeking a highly skilled Data Engineer with strong SQL capabilities and hands-on experience with AWS Glue or equivalent Spark-based tools (e.g., Databricks).

You will be a key contributor in our Data Modernization initiative, helping to design and build scalable data processing pipelines that support our AWS-based data lake. The role involves working with large-scale datasets, optimizing for performance through techniques like partitioning, and delivering clean, reliable data to downstream consumers.

• Develop and maintain robust ETL pipelines using AWS Glue (Apache Spark) or Databricks
• Write complex SQL queries, including Common Table Expressions (CTEs), stored procedures, and views, for data transformation and analysis
• Design and implement effective partitioning strategies in Glue, Athena, and other AWS-native tools to optimize performance and cost
• Ingest, clean, and transform structured and semi-structured data from multiple sources into the AWS data lake
• Collaborate with stakeholders to understand data requirements and deliver well-structured, high-quality datasets
• Troubleshoot performance issues in data pipelines and contribute to tuning and optimization
• Support data governance, lineage, and monitoring initiatives to ensure data quality and reliability

• Excellent SQL skills — advanced experience writing performant queries using CTEs, procedures, and views
• Hands-on experience with AWS Glue (Spark-based ETL), or similar platforms like Apache Spark or Databricks
• Strong understanding of partitioning techniques for large-scale datasets in both databases and data lake environments (e.g., Glue, Athena, Spark)
• Familiarity with cloud data lake architectures and AWS data ecosystem (S3, Athena, Glue, etc.)
• Comfortable working with large volumes of data and optimizing jobs for performance and cost
• Experience in a collaborative environment, with the ability to communicate effectively across technical and non-technical teams
• Financial services experience is a plus, especially familiarity with reference, counterparty, or instrument data

• Pension
• Employee Assistance Programme
• Enhanced Maternity policy
• Give as You Earn
• Cycle to Work Scheme
• Employee Referral Bonus Scheme
• Diversity Networks
• Access to a range of skills and certifications