Finance Technology Data Solutions Engineer

Accountabilities:

• • Build, maintain, and support data solutions for fund accounting, investment operations, and finance reporting.
  • Develop data integrations, transformations, pipelines, and data products using Databricks, Python, PySpark, and SQL.
  • Implement and maintain financial data reconciliations, controls, and validation processes.
  • Work with fund accounting processes including NAV calculation, accruals, corporate actions, fees, and month-end close.
  • Process and integrate investment data covering positions, transactions and trades, security master data, pricing, cash, and general ledger information.
  • Optimize complex SQL queries, data pipelines, and large-scale processing workloads for performance and reliability.
  • Work with cloud-based data platforms and support scalable data engineering solutions.
  • Collaborate directly with US-based stakeholders to understand requirements and deliver effective data solutions.
  • Contribute to data quality, testing, CI/CD, and operational improvements across financial data pipelines.

  Requirements:

  • 10+ years of hands-on data engineering experience, with a strong individual contributor focus rather than team leadership or architecture.
  • Strong, recent hands-on experience with Databricks, including Delta Lake, notebooks, jobs, and workflows; Unity Catalog experience is preferred.
  • Strong understanding of fund accounting processes, including NAV calculation, accruals, corporate actions, fees, and month-end close.
  • Advanced Python and PySpark skills for large-scale data processing.
  • Proven experience delivering data solutions within Financial Services, with Asset Management, Investment Management, Fund Administration, Custody, or Capital Markets experience strongly preferred.
  • Experience developing reconciliations and data controls within financial or regulated environments.
  • Strong understanding of investment data, including positions, transactions, security master, pricing, cash, and general ledger data.
  • Expert SQL skills, including complex joins, window functions, and performance tuning.
  • Experience with at least one cloud platform, such as Azure or AWS.
  • Strong written and spoken English, with confidence communicating directly with US stakeholders.
  • Databricks Data Engineer or Azure/AWS data engineering certification is a plus.
  • Experience with Azure Data Factory, Airflow, Databricks Workflows, or Fivetran is beneficial.
  • Familiarity with Snowflake, dbt, Power BI, or Tableau for downstream reporting is a plus.
  • Experience with Git, Azure DevOps, GitHub Actions, CI/CD, and unit testing for data pipelines is beneficial.
  • Finance Management and a BE, BTech, or MCA qualification are advantageous.

  Benefits:

  • Fully remote working model.
  • Part-time or full-time employment options.
  • Opportunity to work on financial data solutions supporting fund accounting and investment operations.
  • Direct collaboration with US-based stakeholders.
  • Exposure to Financial Services and asset management data environments.
  • Hands-on work with Databricks, cloud data platforms, Python, PySpark, and modern data engineering technologies.
  • Opportunity to contribute to data solutions involving reconciliations, controls, reporting, and regulated financial processes.