Azure Data Engineer

Financial Services / Capital Markets | Data Engineering | Azure

James Adams Group are currently working with a leading organisation within the Financial Services / Capital Markets sector that is expanding its Data function and looking to appoint an experienced Azure Data Engineer to join a newly established data team.

This is an exciting opportunity to become a key member of a growing team, working on a complex data engineering programme involving large, multi-source datasets and highly critical financial information.

The primary focus of the role will be to design and build resilient, scalable and reusable data pipelines, transforming raw data into trusted, structured and auditable data assets.

You will work with data from a variety of sources, including multiple systems and platforms and third-party data providers, supporting the delivery of high-quality data for portfolio analytics, asset strategy, finance and risk.

The role would suit someone who has experience working within a growing Data function and understands the flexibility and adaptability required during the early stages of building a new team. You’ll be comfortable working in a fluid environment, where priorities can evolve and there is an opportunity to help shape both the role and the wider team as the function develops.

Key Responsibilities

• Act as a technical subject matter expert across Azure Data Factory (ADF), Databricks, Python, PySpark and Spark SQL.
• Design, develop and maintain resilient and reusable data pipelines.
• Lead the collection and ingestion of raw data into corporate data platforms and assets.
• Manage data ingestion and integration processes from source through to target, including data warehouses and data lakes.
• Work with the wider Data team to establish and maintain data flows, standards and best practices.
• Build trusted datasets that support portfolio analytics, asset strategy, finance and risk functions.
• Performance-tune and optimise data ingestion and integration processes.
• Work closely with Data Stewards and Business Analysts to understand data requirements and develop effective pipeline solutions.
• Identify opportunities to improve data quality, scalability, performance and reliability.
• Ensure solutions are aligned with the organisation's target-state Data Architecture.
• Contribute to the development of a modern, governed and scalable data engineering environment.