Senior Data Engineer
Summary
Senior Data Engineer who designs, builds, and maintains cloud-based data platforms and ETL/ELT pipelines supporting reporting, analytics, and AI initiatives. Works across legacy and modern stacks — Oracle/SQL Server, Python, Azure Data Factory, Synapse, Spark — with a focus on performance tuning and reliable data flows.
As a Senior Data Engineer, you design, build, and maintain cloud-based data platforms and pipelines to enable efficient data collection, processing, and analytics. You will work across legacy and modern environments, ensuring scalable, reliable data flows and optimising performance and cost. You’ll contribute to data architectures, warehouses, and data lakes that support reporting, analytics, and AI initiatives, while staying aligned with security and reliability standards. This role offers the chance to influence data strategy in a hybrid, collaborative setting and to modernise critical data infrastructure.
Responsibilities- Design, implement, and maintain ETL/ELT pipelines ingesting data from diverse sources
- Monitor overnight loads, resolve failures, and implement automated alerts for timely data availability
- Contribute to design and optimisation of data architectures, warehouses, and data lakes for analytics and AI
- Tune system, pipeline, and query performance to improve efficiency and scalability
- Leverage modern data engineering tools and frameworks (e.g., Azure Data Factory, Synapse, Spark, Python) and evaluate new technologies
- Maintain legacy data warehouses and pipelines until replaced by modern data platform tooling
- Significant experience in data engineering across traditional and cloud platforms
- Proven track record designing and maintaining scalable data architectures and pipelines
- Experience delivering in complex data-driven environments emphasising security and reliability
- Proficiency in Oracle DBMS/SQL Server, Python, SQL, T-SQL/PLSQL, SSIS, SAP Data Services
- Experience with cloud platforms (Azure, AWS, Snowflake) and data tools (Azure Data Factory, Synapse, Spark, Notebooks)
- Knowledge of source control (Git) and DevOps practices
- Ability to design, maintain, and optimise scalable ETL/ELT pipelines
- Strong analytical and problem-solving abilities
- Ability to troubleshoot data issues and monitor performance
- strong analytical and problem-solving abilities
- ability to troubleshoot complex data issues
- focus on performance tuning and scalability
- Oracle DBMS/SQL Server
- Python
- SQL