Senior Compliance Tech Analyst, Platform (Compliance Automation)
You will build and maintain end to end data pipelines powering compliance detection and decisioning You will improve signal quality define control performance metrics and create scalable tooling that makes compliance data trustworthy and auditable You will translate regulatory requirements into robust data structures and features
Responsibilities
- Build and maintain curated datasets and data models that power compliance controls across Transaction Monitoring EDD/KYC and Screening systems
- Own data quality for compliance datasets by implementing validation checks monitoring lineage tracking and documentation to ensure outputs are accurate complete and audit-ready
- Partner with cross functional engineering teams and Compliance stakeholders to close upstream data gaps standardize instrumentation and translate control requirements into scalable data structures and feature sets
- Drive detection signal quality improvements by analyzing detection outputs identifying opportunities to reduce non-actionable noise while protecting sensitivity and defining success metrics for controlled rollouts
- Execute measurement frameworks for compliance control effectiveness including coverage timeliness stability and outcome-based metrics and build repeatable reporting pipelines consumable by Compliance leaders operations teams and auditors
Requirements
- 3-5 years of experience in analytics engineering data engineering or data-heavy technical roles
- Advanced SQL proficiency including complex transformations performance tuning and data quality checks
- Experience building and maintaining ETL/ELT pipelines and data models using tools such as dbt Airflow or equivalent orchestration/transformation frameworks
- Demonstrated ability to execute on ambiguous cross-functional projects in regulated environments with clear written and verbal communication
- Python skills applied to automation pipeline development and data analysis
- Utilizes generative AI responsibly maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency cost and quality