Databricks Python Data Engineer - FS/Trading - 12 months at La Fosse Associates Limited, London, £600-£650 per day

Data Engineer | Databricks, Python | Financial Markets & Trading | London/Hybrid | 12 month contract

Location: London (Flexible Hybrid model) circa 1-2 day p/w in office

IR35: Outside

A leading, global financial services firm is seeking an experienced Data Engineer to join their expanding Capital Markets technology team. This is an opportunity to work on a large-scale data transformation programme, developing robust data platforms that services a range of key areas including Front Office trading, risk, regulatory reporting, and market data analytics.

Working alongside stakeholders across Trading, Risk, Quantitative Research and Technology, you will design and build scalable data solutions that enable critical business decisions across global markets.

Key Responsibilities

• Design, develop and optimise enterprise-scale data pipelines and platforms
• Build and maintain data solutions supporting capital markets and a global trading functions
• Develop cloud-native data engineering solutions using modern data technologies
• Collaborate with business and technology stakeholders to deliver strategic data initiatives
• Drive best practices across data quality, governance, performance and automation

Required Experience

• Strong Data Engineering background within Banking, Financial Services or Capital Markets.
• Expertise in Python and SQL.
• Experience with Spark, PySpark and streaming technologies
• Experience with cloud data platforms such as Databricks and Azure Data Services.
• Strong understanding of ETL/ELT development and modern data architectures.
• Experience working with large-scale financial datasets.
• Excellent stakeholder management and communication skills

Desirable Experience

• Sector knowledge such as asset classes including Equities, Fixed Income, FX or Derivatives
• Exposure to data projects for Front Office trading systems, market data or risk platforms.

If you're an experienced Data Engineer looking to apply your expertise within a fast-paced, challenging, financial environment, we'd be keen to speak with you.