Senior Data Engineering

• Expert-level proficiency in AWS cloud services including S3, Glue, Athena, Lake Formation, and CloudFormation, with hands-on experience designing and operating cloud-native data platforms.
• Strong Python programming skills at a senior level, applied to data engineering, pipeline development, and automation.
• Solid experience with ETL/ELT frameworks, data transformation patterns, and data quality tooling (e.g., Great Expectations, dbt, or similar).
• Working knowledge of Snowflake for data warehousing, query optimisation, and integration within broader data ecosystems.
• Experience with Apache Iceberg or similar open table formats for managing large-scale, versioned analytical datasets.

Some other highly valued skills may include:

• Experience with Apache Airflow or similar workflow orchestration tools for scheduling and monitoring complex data pipelines.
• Familiarity with IAM, permissions management, and data access governance within AWS (Lake Formation policies, resource-based policies, role-based access).
• Understanding of data cataloguing and metadata management practices to support discoverability and governance of enterprise datasets.
• Experience with Databricks or Starburst for distributed data processing and federated query engines.
  • Ability and willingness to collaborate with diverse internal teams across technology, data, and business functions to drive adoption and alignment.