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Mid-level role, known employer and common data-engineering skills raise competition despite finance specialization.
Requires finance/fund-accounting domain expertise and reconciliation controls, reducing cross-industry portability.
Explicit 5-8 years and mandatory Databricks/SQL/Python requirements make screening stringent.
Design, develop, and maintain Finance Technology data solutions supporting Fund Accounting processes, including transformations, integrations, validations, and controls.
Build scalable data products and ensure data quality, reconciliation, and exception management for Fund Accounting operational and downstream use cases.
Collaborate with Enterprise Data Engineering and other teams to align Finance Technology data solutions with enterprise standards and deliver governed data products used across reporting and analytics.
5 to 8 years of hands-on data engineering or financial technology experience in financial services or controlled enterprise data environments.
Advanced skills in SQL Server, Databricks (notebooks, workflows, Spark, Delta Lake), and Python/PySpark for ETL/ELT and data transformations.
Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or related field (or equivalent experience).
Experience with Git, automated testing, CI/CD, and disciplined software delivery practices.
Experienced in Fund Accounting-specific data integrations, reconciliations, and controls within financial services or asset management contexts.
Strong operator who can own end-to-end technical delivery within a multi-team enterprise data ecosystem while maintaining domain accountability.
Proficient in building governed, reusable, scalable data products supporting dashboards, reports, extracts, and operational workflows in a controlled environment.