Data Engineer – Capital Markets | Cloud Data Platforms
La Fosse Associates
A complete application in a minute — tailored resume and cover letter, ready to send.
Job summary
La Fosse Associates in London is seeking an experienced Data Engineer to join the Capital Markets technology team on a 12-month contract in a flexible hybrid model. You will design and build scalable data platforms supporting front-office trading, risk, regulatory reporting and market data analytics.
Responsibilities include designing data pipelines, working with Python/SQL, Spark/PySpark, and cloud platforms like Databricks and Azure Data Services, and collaborating with stakeholders to deliver
Qualifications
- 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.
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.
Skills
Tools
Job description
La Fosse Associates in London is seeking an experienced Data Engineer to join the Capital Markets technology team on a 12-month contract in a flexible hybrid model. You will design and build scalable data platforms supporting front-office trading, risk, regulatory reporting and market data analytics.
Responsibilities include designing data pipelines, working with Python/SQL, Spark/PySpark, and cloud platforms like Databricks and Azure Data Services, and collaborating with stakeholders to deliver
'/%3e%3cpath%20d='M101.744%2012.4726L102.894%2016.1947L99.0021%2013.2201L101.744%2012.4726ZM105.3%208.40937H100.488L99.0026%203.59473L97.5116%208.41047L92.7%208.40385L96.5965%2011.3834L95.1055%2016.1942L99.0021%2013.2196L101.408%2011.3834L105.3%208.40992V8.40937Z'%20fill='white'/%3e%3cdefs%3e%3clinearGradient%20id='paint0_linear_5593_1381'%20x1='90'%20y1='9.44471'%20x2='99'%20y2='9.44471'%20gradientUnits='userSpaceOnUse'%3e%3cstop%20stop-color='%2300AD70'/%3e%3cstop%20offset='0.998594'%20stop-color='%2300B67A'/%3e%3cstop%20offset='1'%20stop-color='%23DCDCE6'/%3e%3c/linearGradient%3e%3c/defs%3e%3c/svg%3e){kind=small}
