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Senior Data Analyst, RegTech

DriveWealth
CompanyDriveWealth
CategoryData & Analytics
LocationOffice - Chicago; Office - NYC
RemoteOn-site (inferred)
EmploymentNot stated
LevelSenior
SalaryNot stated by the employer
Posted29 Mar 2026
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
About Us DriveWealth is on a mission to make investing easier. We believe that everyone should have the ability to control their financial future, and that access to financial markets should not be limited by geography, wealth, or legacy systems. We are a global B2B financial technology organization dedicated to democratizing access to financial independence around the world. Our mission is realized through an API-based platform, empowering our partners to offer seamless investing and trading experiences to clients worldwide, all from their mobile devices. Our technology provides partners with a modern, extensible toolkit, enabling traditional investment workflows and innovative techniques like fractional share ownership. DriveWealth has evolved into a global platform offering trading of US equities, mutual funds, ETFs, fixed income, and options. There’s never been a better time to build a category-defining business and there has rarely been a team better positioned for this opportunity. Our culture blends the pace and agility of a fintech start-up with the impact, stability, and discipline of Wall Street. We encourage creativity and experimentation while ensuring institutional-grade execution and regulatory compliance in everything we do. Join us and help build the future of global investing! About The Role The RegTech team at DriveWealth develops data products essential for our compliance department to meet all regulatory obligations. We are seeking a Senior Data Analyst to focus on the creation, maintenance, and monitoring of highly curated data marts, feeds, and dashboards for both internal compliance and external regulatory reporting. The ideal candidate must possess a deep understanding of the trade lifecycle and have a proven track record of collaboration with data engineers, product managers, and regulatory stakeholders. The role entails ownership of data quality, including defining quality standards, developing and implementing comprehensive testing strategies, and establishing robust data governance frameworks to ensure accuracy, integrity, and compliance across all regulatory data assets. What You’ll Do Support Ad-Hoc Inquiries and Regulatory Exams: Respond quickly and accurately to ad-hoc data requests and regulatory examination inquiries from Compliance and Legal teams, providing data and analysis as needed. Own the Regulatory and Supervisory Data Layer: Architect, build, and maintain data marts and Sigma reports used for critical regulatory functions (e.g., CAT, EBS, trade monitoring, AML) and internal compliance supervisory monitoring, ensuring consistent, accurate outputs delivered quickly through efficient code with robust testing and verification. Drive Optimization and Efficiency: Continuously evaluate and optimize data models, SQL queries, and Sigma reports for performance, cost-efficiency, and scalability, contributing to a best-in-class RegTech data infrastructure Proactively Detect and Report Upstream Data Anomalies: Establish monitoring and alerting to proactively detect, analyze, and escalate upstream data anomalies and pipeline failures, providing daily exception reports to upstream data producers.   Own the Business Logic Layer: Define, implement, and rigorously document the core business logic and transformations within the data marts to ensure accurate calculation and aggregation for all regulatory and supervisory metrics. Monitor Inbound Regulatory Files and Feeds: Establish and maintain robust monitoring for all critical inbound regulatory data files and real-time feeds, ensuring timely arrival, data quality, and correct ingestion into the data ecosystem. Translate Regulation to Data: Work directly with business partners and Compliance to translate new regulatory rules, changes, and reporting obligations into precise analytics engineering requirements and data flows. Lead Comprehensive Data Testing: Team with QA
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