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Mid-level data engineering role with broad skills and metro appeal, leading to high candidate competition.
Role requires fund accounting knowledge, reconciliations, and finance domain expertise, limiting cross-industry transferability.
Explicit 5-8 years and mandatory Databricks, SQL Server, Python/PySpark and finance-domain experience make filters strict.
Design, build, deploy, and support domain-specific Finance Technology data solutions for Fund Accounting processes including transformations, reconciliations, and controls.
Develop and maintain scalable data products and integrations supporting accounting operations, reporting, analytics, and workflows using technologies like SQL Server, Databricks, Python, and PySpark.
Collaborate with enterprise data engineering and cross-functional teams to ensure alignment, data quality, operational support, and adherence to engineering standards across data solutions.
Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or related field (or equivalent experience).
5 to 8 years of hands-on experience in data engineering, data solutions, or financial technology, preferably in financial services or controlled enterprise data environments.
Advanced SQL Server skills (queries, stored procedures, performance tuning) and hands-on Databricks experience (notebooks, workflows, Spark, Delta Lake).
Proficiency in Python/PySpark for data transformations, validations, automation, and testing.
Experienced in building and owning finance domain-specific data transformations, integrations, validation, reconciliation, and monitoring solutions within a complex enterprise environment.
Skilled at collaborating with cross-functional teams to integrate Fund Accounting data requirements into enterprise data platforms and delivering governed, scalable data products.
Disciplined in software engineering best practices including Git, peer reviews, automated testing, CI/CD, secure deployments, and operational support for data pipelines.