What are the responsibilities and job description for the Risk&Compliance - Data Engineer (Architect) || Hybrid at Lake Mary, FL position at IT First Source?
Job Details
Data Engineer (Architect) - Risk & Compliance (AML) | Hybrid at FL
Ideal candidate should have:
- Minimum 15 years experience with a deep history on Data Architecture (not infrastructure)
- Recent and at least 5 years experience in Risk, Compliance, and Financial Crimes Domain Expertise (AML, Compliance, Sanctions).
- Data Governance, Security, and Compliance
Job Summary:
We are seeking a Data Engineer (Architect) with deep expertise in Risk & Compliance, Sanctions Screening, and Anti-Money Laundering (AML) to lead the design and development of scalable data solutions supporting financial crime detection and regulatory compliance.
This role requires strong architectural skills to design high-performance data platforms, optimize data pipelines, and ensure regulatory alignment. The ideal candidate has extensive experience with big data architectures, cloud platforms, and data security best practices while collaborating closely with cross-functional teams.
Key Responsibilities:
Data Architecture & Solution Design:
- Define and implement end-to-end data architecture for risk and compliance systems ensuring scalability, security, and performance.
- Design data models, pipelines, and frameworks to support Sanctions Screening, AML Transaction Monitoring, KYC, Fraud Analytics, and Regulatory Reporting.
- Develop highly available, fault-tolerant architectures for processing large-scale, real-time financial transactions.
Data Governance & Compliance:
- Ensure data integrity, quality, security, and privacy across all risk and compliance systems.
- Implement data governance frameworks aligned with global financial regulations (FATF, OFAC, FinCEN, GDPR).
- Establish audit trails, access controls, and encryption to meet security and regulatory standards.
Performance Optimization & Automation:
- Optimize query performance, indexing strategies, and distributed computing for large-scale datasets.
- Automate ETL/ELT pipelines, data validation, and reconciliation processes to improve accuracy and efficiency.
- Implement AI/ML-driven anomaly detection for fraud and risk management.
Collaboration & Leadership:
- Partner with Risk, Compliance, AML, and Fraud teams to define data requirements and align technology solutions with business objectives.
- Manage product backlog through to delivery.
- Provide technical leadership and mentorship to data engineers, ensuring adherence to best practices in data architecture and security.
- Engage with executive leadership and stakeholders, delivering strategic insights and technical recommendations.
Thanks,
IT First Source
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