Analytics Engineer

Job title: Analytics Engineer
Location: Pittsburgh, PA (Onsite)
Employment Type: Contract
Remote: No
Work Experience Required: 10-15 Years

Engineering Analytics 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 in Surveillance & Markets Engineering Analytics Hands-on implementation with TradingHub, NICE Actimize, Nasdaq SMARTS, Behavox, SteelEye, 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.

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