Finance Technology Data Solutions Engineer
Quick Summary
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,
This role offers the opportunity to build and support data solutions powering fund accounting, investment operations, and financial reporting for a US-based asset management environment. You will work across data integrations, transformations, reconciliations, controls, and data products that support critical financial processes. The position requires strong hands-on expertise with Databricks, Python, PySpark, and SQL to process and manage large-scale financial data. You will apply your understanding of fund accounting, investment data, and financial services to deliver reliable and well-controlled solutions. Working as an individual contributor, you will collaborate directly with US stakeholders and contribute to data engineering initiatives in a regulated environment. The role is available on a part-time or full-time remote basis.
- 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
~2 min read- 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.
What We Offer
~1 min readLocation & Eligibility
Listing Details
- Posted
- September 28, 2026
- First seen
- September 28, 2026
- Last seen
- September 28, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 68%
- Scored at
- September 28, 2026
Signal breakdown
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