Lead Data Engineer

Job not on LinkedIn

🕒 July 15

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 23%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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UFS Tech

WebsiteLinkedInAll Job Openings

201 - 500 employees

🏦 Banking

💳 Fintech

🔒 Cybersecurity

💰 $19.9M Venture Round - UFS on 2019-05

Banking • Fintech • Cybersecurity

UFS Tech is a technology and services provider focused on empowering community banks. It delivers core banking and digital banking platforms, payments, cash management, and customer engagement tools alongside managed IT services (private cloud, hosted email, end-user support), cybersecurity offerings (virtual firewall management, vulnerability management, SureProtect/SureWatch), backup and disaster recovery, document imaging and delivery, and advisory services for IT, information security, and regulatory compliance. UFS positions itself as a partner to community banks, offering purpose-built, modular solutions and professional services to help banks operate securely, meet regulatory requirements, and grow customer relationships.

📋 Description

• 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

🎯 Requirements

• 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