Job Title: Data Engineer with ETL & Surveillance & Marketing Analytics
Location: Pittsburgh, PA
Duration: Long-term Contract
Job Description:
- ETL with Surveillance & Markets Engineering Analytics P2C3STS Lead onboarding of surveillance use cases, venues, products, and data sources; translate business and regulatory requirements into scalable data solutions.
- Serve as SME for market manipulation, insider trading, front running, spoofing/layering, wash trading, employee trading, and information barrier monitoring.
- Support model tuning, calibration, effectiveness reviews, regulatory examinations, audits, and model validation.
- Design scalable pipelines and end-to-end architecture for order, execution, position, market, reference, employee, and communications data.
- Lead source integration and optimize ETL/ELT for large-scale surveillance datasets, ensuring performance, resiliency, stability, and scalability.
- Drive cloud-native architecture and surveillance platform modernization.
- Lead profiling, gap assessments, complex investigations, root cause analysis, reconciliation, trend analysis, and surveillance data validation.
- Establish controls and metrics for completeness, accuracy, timeliness, consistency, reconciliation, lineage, and traceability; maintain source-to-target mappings and business rules.
- Develop KPIs and monitoring dashboards; partner with analysts to improve alert quality and reduce false positives.
- Ensure enterprise data-governance compliance, audit readiness, regulatory reporting, and controls aligned with SEC, FINRA, FCA, CFTC, and global obligations.
- Partner with Product Owners and Program Managers on roadmaps and provide technical oversight across surveillance initiatives.
- Experience Surveillance & Markets Engineering Analytics
- Hands-on implementation with Trading Hub, NICE Actimize, Nasdaq SMARTS, Behavox, Steel Eye, ACA SIGMA, eFlow, or an equivalent surveillance platform.
- Regulatory knowledge of SEC, FINRA, CFTC, FCA, MAR, MiFID II, and Dodd-Frank
- Experience with AI/ML and large language model applications in Compliance and Surveillance, cloud-native architectures, and data observability platforms.
- Accelerate onboarding of data sources and surveillance scenarios while increasing coverage across products, markets, and business lines.
- Improve data quality, operational controls, traceability, lineage, audit readiness, and surveillance effectiveness; reduce defects and regulatory findings.
- Serve as the primary technical liaison across Compliance, Surveillance Operations, Product, Architecture, and Engineering.