4 of 4 Remote/Hybrid Complex ETL Jobs in London

Code deployment tools. Validate data for completeness and correctness; ensure ETL code meets expectations. Communicate status, issues, and blockers to project managers and ETL team leads. Identify and solve opportunities for continuous improvement of ETL interfaces. Update and publish documentation, system diagrams, and project plans. Attend project … and ETL meetings; conduct knowledge transfer sessions. Assist Production support teams with resolving production incidents related to ETL processes as needed. Skills & Experience: Several years of hands-on experience with IBM DataStage and various versions. Involvement in full project life cycles, from requirements gathering to deployment and maintenance ...

pipelines, models, and performance. In this role, you will: Design, build, and maintain scalable data pipelines in Azure and Snowflake Develop and optimise ETL and ELT processes for batch and micro-batch workloads Build and enhance enterprise data warehouse models Write and optimise complex SQL queries … preferred) Strong expertise in Azure Data Factory, Azure SQL, Azure Storage, Azure Functions, and Snowflake (1+ year) Advanced SQL skills, including complex ETL and dimensional/data modeling Experience building batch and micro-batch data pipelines Deep understanding of enterprise data warehouse architecture and methodologies Experience working ...

Snowflake . This role is central to powering our BI, analytics, and AI/ML initiatives. The Role Build & Integrate: Develop complex ETL/ELT pipelines and implement OneLake interoperability between Fabric and Snowflake. Architect: Operate a Medallion architecture (Bronze/Silver/Gold) and design curated ...

code (Base SAS, Macros, DI Studio) to PySpark using automated tools (SAS2PY) and manual refactoring. Pipeline Engineering: Design, build, and troubleshoot complex ETL/ELT workflows and data marts on AWS. Performance Tuning: Optimise Spark workloads for execution efficiency, partitioning, and cost-effectiveness. Quality Assurance: Implement clean … Glue Workflows. SAS Knowledge (P1): Solid foundation in SAS to enable the understanding and debugging of legacy logic for conversion. Data Modeling: Expertise in ETL/ELT, dimensions, facts, SCDs, and data mart architecture. Engineering Quality: Experience with parameterisation, exception handling, and modular Python design. Additional Details Industry: Financial ...