Finance Technology Data Solutions Engineer:

The client's non-negotiables are strong technical skills plus Asset Management experience, or at minimum very strong Financial Services experience.

• 10+ years of hands-on data engineering. This is an individual contributor role, not a team lead or architect role.
  
• Strong, recent hands-on experience with Databricks (Delta Lake, notebooks, jobs/workflows; Unity Catalog preferred).
  
• Understanding of Fund Accounting processes: NAV calculation, accruals, corporate actions, fees, month-end close.
  
• Strong Python and PySpark for large-scale data processing.
  
• Proven delivery of data solutions in Financial Services. Asset Management, Investment Management, Fund Administration, Custody or Capital Markets is strongly preferred.
  
• Experience building reconciliations and data controls in a finance or regulated environment.
  
• Working knowledge of investment data: positions, transactions/trades, security master, pricing, cash and general ledger.
  
• Expert SQL: complex joins, window functions, performance tuning
  
• Experience with at least one cloud platform (Azure or AWS).
  
• Clear written and spoken English, with confidence working directly with US stakeholders.
  

• Databricks Certified Data Engineer (Associate or Professional), or Azure/AWS data engineering certification.
  
• Orchestration and integration tools: Azure Data Factory, Airflow, Databricks Workflows, Fivetran.
  
• Snowflake, dbt, or Power BI/Tableau for downstream reporting.
  
• CI/CD with Git and Azure DevOps or GitHub Actions; unit testing for data pipelines.
  
• Finance Management plus BE , BTech, or MCA is a plus.
  

Originally posted on Himalayas