Data Engineer - Azure, Databricks, Python, C#, SQL, ETL - Data Platform - Financial Services
Data Engineer - Financial Services - Azure, Databricks, Snowflake, Hadoop, Fabric, Python, SQL - Data Platform
Must have: 6+ years in data engineering, a consistent financial services background, end-to-end data pipelines, strong SQL
Our client, a global investment and corporate bank, requires a Data Engineer to help build a greenfield hybrid Azure data platform and migrate Legacy capability onto it. A consistent financial services pedigree is the key requirement; the specific platform is flexible. Experience with Databricks, Snowflake, Cloudera/Hadoop or Microsoft Fabric is all relevant, and real strength in one area can make up for gaps in another. Capital markets knowledge is a real bonus.
you'll be:
- Building data pipelines, ETL and integrations on a modern cloud data platform
- Developing data models and architecture (lakehouse, data lake, data fabric)
- Integrating data from databases, APIs and message bus platforms
- Owning data quality, performance tuning and governance
- Owning CI/CD and automated testing
- Mentoring and peer reviewing
Required: 6+ years of data engineering in financial services, a modern data platform (Databricks, Snowflake, Cloudera/Hadoop or Fabric), Python or C#, SQL, Oracle/MS SQL
Desirable: Databricks, Azure, NoSQL, APIs, message bus technology, Scala/Java, Docker,
Kubernetes, Denodo, Agile
London Based/Hybrid
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