Data Engineer with ETL & Risk & Trade

Job Description

Hi,

Role: Data Engineer with ETL & Risk & Trade

Location: Pittsburgh, PA {3days onsite 2 days remote}

Job Description :

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• Skill, ETL with Surveillance & MarketsEngineeringAnalyticsP2C3STSLead onboarding of surveillance use cases, venues, products, and data sources; translate business and regulatory requirements into scalable data solutions.
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• Serve as SME for market manipulation, insider trading, front running, spoofing/layering, wash trading, employee trading, and information barrier monitoring.
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• Support model tuning, calibration, effectiveness reviews, regulatory examinations, audits, and model validation.
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• Design scalable pipelines and end-to-end architecture for order, execution, position, market, reference, employee, and communications data.
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• Lead source integration and optimize ETL/ELT for large-scale surveillance datasets, ensuring performance, resiliency, stability, and scalability.
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• Drive cloud-native architecture and surveillance platform modernization.
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• Lead profiling, gap assessments, complex investigations, root cause analysis, reconciliation, trend analysis, and surveillance data validation.
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• Establish controls and metrics for completeness, accuracy, timeliness, consistency, reconciliation, lineage, and traceability; maintain source-to-target mappings and business rules.
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• Develop KPIs and monitoring dashboards; partner with analysts to improve alert quality and reduce false positives.
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• Ensure enterprise data-governance compliance, audit readiness, regulatory reporting, and controls aligned with SEC, FINRA, FCA, CFTC, and global obligations.
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• Partner with Product Owners and Program Managers on roadmaps and provide technical oversight across surveillance initiatives.
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• Experience Surveillance & Markets Engineering Analytics Hands-on implementation with TradingHub, NICE Actimize, Nasdaq SMARTS, Behavox, SteelEye, ACA SIGMA, eFlow, or an equivalent surveillance platform.
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• Regulatory knowledge of SEC, FINRA, CFTC, FCA, MAR, MiFID II, and Dodd-Frank.
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• Experience with AI/ML and large language model applications in Compliance and Surveillance, cloud-native architectures, and data observability platforms.
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• Accelerate onboarding of data sources and surveillance scenarios while increasing coverage across products, markets, and business lines.
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• Improve data quality, operational controls, traceability, lineage, audit readiness, and surveillance effectiveness; reduce defects and regulatory findings.
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• Serve as the primary technical liaison across Compliance, Surveillance Operations, Product, Architecture, and Engineering.
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Work Experience 10-15Years