Build and support fund accounting data solutions for asset management, including integrations, transformations, reconciliations, controls, and finance reporting products. Develop large-scale data pipelines using Databricks, Python, PySpark, and SQL; work with investment data, NAV calculations, accruals, corporate actions, fees, and general ledger information. Support cloud-based delivery, data quality, orchestration, CI/CD, and direct collaboration with US stakeholders.
This is a remote position.
Finance Technology Data Solutions Engineer:
We need a hands-on data engineer to build and support Fund Accounting data solutions for a US-based Asset Management client. The work covers data integrations, transformations, reconciliations, controls and data products that support fund accounting, investment operations and finance reporting. This is WFH part-time or full-time position.
Must-have skills and experience
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.
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