Note: The job is a remote job and is open to candidates in USA. UFS Tech is a trusted technology and services partner for community financial institutions, and they are seeking a Lead Data Engineer to own the Navanta data backbone. This role involves designing and building a reliable data architecture that supports AI platforms and ensures data quality and compliance.
Responsibilities
- Design the lakehouse: Apache Iceberg (or similar technology) on object storage, a catalog for table management and per-bank isolation, dbt models, and a query engine
- Build secure, least-privilege ingestion from bank systems — log-based CDC where permitted, with query-based and batch/SFTP fallbacks, plus an in-bank collector pattern
- Own data modeling for the semantic and metric layer (deposits, concentration, uninsured exposure, asset quality, and peer groups)
- Handle schema drift, data quality, and reconciliation; make ingestion observable and recoverable
- Partner with the AI/ML team on the structured-query path and with Security on PII classification at landing, in alignment with regulatory data-handling requirements
- Document data lineage, transformation logic, and access controls to support audit and exam readiness
- Define and enforce data contracts, quality thresholds, and alerting for pipeline failures
Skills
- 8–12+ years in data engineering with end-to-end ownership of ingestion through serving, and 2+ years in a lead or senior role
- Strong Python and expert SQL; rigorous data modeling for analytics
- Hands-on lakehouse experience (Iceberg/Delta/Hudi or equivalent) and modern transformation tooling
- Built reliable pipelines from messy operational and transactional source systems
- Comfort with CDC mechanics and the realities of pulling from databases you do not control
- Bachelor's degree in computer science, mathematics, information systems, or a related field, or equivalent hands-on experience
- Experience in the financial services industry or a regulated data environment strongly preferred
- Experience with financial or core-banking data, or FFIEC / Call Report data specifically
- Strong SQL Server familiarity
- Data contracts, lineage, and governance practices
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