Role & responsibilities:

Hands-on engineering role responsible for supporting and operating the enterprise Azure and Databricks data platform.

This role works closely with Data Platform Engineering, Data Ingestion & Integration, Data Engineering & Data Products, and Data Distribution Services teams to ensure the platform remains secure, scalable, reliable, and optimized.

- Develop and maintain scalable data pipelines, ETL/ELT processes, and data integrations.

- Assist with building and optimizing cloud-based data solutions and enterprise data platforms.

- Work closely with global teams on design, architecture and build out of data platform.

Preferred candidate profile:

- 6 - 8+ years of hands-on data engineering, data solutions, or financial technology experience, ideally within financial services, asset management, accounting, investment operations, or another controlled enterprise data environment.

- Hands-on experience designing, developing, deploying, and supporting enterprise-scale data pipelines using Azure Databricks, PySpark, Delta Lake, Python, SQL, and Azure Data Factory, including both batch and streaming workloads.

- Hands-on Databricks experience, including notebooks, workflows/jobs, Spark concepts, Delta Lake patterns, and production support.

- Python and/or PySpark for transformation, validation, automation, and testing.

- Strong ETL/ELT, data modeling, integration, and curated-data-layer experience.