Data Engineer (Azure)
Working for a renowned financial services organisation
Your new role
Seeking a Data Engineer to help design and maintain scalable batch and near‑real‑time ingestion pipelines, modernizing legacy ETL/ELT processes into Azure and Snowflake, and implementing best‑practice patterns such as CDC, incremental loading, schema evolution, and automated ingestion frameworks. They build cloud‑native solutions using Azure Data Factory/Synapse, Databricks/Spark, ADLS Gen2, and Snowflake capabilities including stages, file formats, COPY INTO, and Streams/Tasks to support raw‑to‑curated data modelling.
The role involves creating reusable components and Python libraries to accelerate delivery across teams, enforcing data quality through validation, observability, and robust pipeline design, and ensuring strong security, governance, and documentation standards. Collaboration within agile workflows-including CI/CD, code reviews, and iterative planning-is also key to delivering consistent, reliable, and secure data solutions.
What you'll need to succeed
Strong hands-on data engineering experience, with strong focus on data ingestion
Experience building production pipelines using Azure Data Factory, Databricks, Synapse
Solid SQL skills and experience working with modern cloud data warehouses, ideally Snowflake
Proficiency in Python for data processing, automation, and pipeline utilities
Good understanding of data lake/lakehouse concepts and ingestion patterns
Infrastructure-as-Code exposure (Terraform) and CI/CD (Azure DevOps)
Able to prototype quickly while adhering to Group standards and controls
Communicates clearly with business stakeholders and technical teams
Familiarity with orchestration frameworks (Dagster) - desirable
Energy commodity trading experience is a real advantage
What you'll get in return
Flexible working options available.
What you need to do now
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.
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