Assoc. Principle Data Analytics Engineer

What you’ll own

• Build and maintain automated workflows that extract, process, and transform data into scalable, standardized models
• Develop end-to-end data pipelines that improve automation across compliance and control-related programs
• Create dashboards, monitoring solutions, and reporting tools that support ongoing surveillance and program oversight
• Deliver sustainable, executive-level reporting for leadership, the Chief Compliance Officer, the Board, and regulatory audiences
• Improve analytics processes by identifying smarter, faster, and more scalable ways to leverage data
• Partner with cross-functional stakeholders and subject matter experts to gather requirements, access source data, and deliver meaningful solutions
• Support a best-in-class analytics framework through strong testing, code review, documentation, and technical rigor
• Recommend architecture-level improvements that enhance long-term efficiency, governance, and decision-making

What makes you a strong fit

• You bring strong hands-on experience in data analytics engineering, automation, and pipeline development
• You are highly skilled in SQL and comfortable working with large, complex datasets
• You have experience with Python, R, or Matlab for data analysis, transformation, and visualization
• You know how to connect and extract data from REST APIs and source systems
• You’ve built dashboards and reports in Tableau or similar BI tools
• You understand data architecture, data modeling, semantic modeling, and scalable reporting design
• You’re comfortable working in environments that value CI/CD, DevOps principles, Agile delivery, and version control
• You can translate technical work into business impact and communicate effectively with both technical and non-technical stakeholders
• You thrive in fast-paced environments, manage competing priorities well, and know how to deliver quality solutions under deadlines

Tools and technology

• Python (Pandas/Numpy), R, or Matlab
• SQL / relational databases
• Tableau or similar visualization tools
• Airflow, Alteryx, Power BI, or other workflow/orchestration tools
• AWS, Azure, or similar cloud platforms
• Git, Agile practices, and data pipeline development best practices
• Exposure to AI tools, generative AI, agentic AI, or prompt engineering is a plus

Preferred background

• 3–5 years of experience in software development, data analytics, or quantitative analysis
• Bachelor’s degree in Computer Science, Information Systems, Mathematics, Finance, or a related field
• Master’s degree preferred
• Experience in fintech, financial services, risk, or compliance is highly valued