Senior Data Analyst, Compliance

Job Description

At Remitly, we believe everyone deserves the freedom to access, move, and manage their money wherever life takes them. Since 2011, we've tirelessly delivered on our promise to customers sending money globally, providing secure, simple, and reliable ways to manage their money, ensuring true peace of mind. Whether it's supporting loved ones back home, growing a business across continents, or pursuing new opportunities abroad, we're not just here to move money— we're here to move our global customers forward.

We're looking for builders, reimaginers, and global thinkers who want to work at the intersection of technology, trust, and transformation. If that's you and you're ready to do the most meaningful work of your career—we invite you to join over 2,800 passionate Remitlians worldwide who are united by our vision to transform lives with trusted financial services that transcend borders.

About the Role

The Sr. Data Analyst, Compliance, is a high-performing individual contributor within the broader analytics team. You will be responsible for bridging the gap between compliance business and technology by translating requirements into well-defined and concrete data products. You will own the "Requirement-to-Reporting" lifecycle, ensuring business requirements are robust and detailed and data engineers build the right foundations, balancing data governance with business flexibility, and delivering the final data products with reliability, predictability, and accuracy.

The Lifecycle You Will Own

• Discovery: Understanding the "Why" behind the business request.
• Mapping: Identifying the "Where" (data sources) and the "Gaps."
• Specs: Writing the "How" for the Data Engineers.
• Validation: Testing the "Truth" of the data through UAT.
• Delivery: Visualizing the "So What" for stakeholders.

Key Responsibilities

• Strategic Translation: Partner with compliance leaders and stakeholders to understand objectives and translate them into Remitly business language and further translate them into detailed functional/technical specifications.
• Metric Definition: Lead the definition of North Star metrics and KPIs, ensuring alignment across different departments to prevent "data silos" or conflicting definitions.
• Documentation: Own the creation of source-to-target mappings, logic flowcharts, and business requirement documents (BRDs).
• Data Scouting: Identify internal and external data sources required to fulfill business needs; perform exploratory data analysis to highlight data gaps or quality issues.
• Engineering Partnership: Work hand-in-hand with Data Engineers to design scalable data pipelines, providing the necessary business logic and transformation rules.
• Validation & UAT: Lead the User Acceptance Testing (UAT) process, rigorously validating transformation logic and data integrity before production deployment.
• Solution Architecture: Design and build sophisticated reporting solutions (Tableau, PowerBI, or internal tools) that go beyond simple charts to tell a meaningful business story.
• Data Consumption: Ensure data is delivered in a "business-consumable" form, prioritizing UX/UI in dashboards to drive high adoption rates among non-technical users.

Typical Qualifications

• Experience: 4-8+ years in a Senior Analyst or Analytics Consultant role, specifically focused on the end-to-end delivery of data products.
• Problem Solving: Mastery of First Principles Thinking—the ability to take a vague request like "we need to increase retention" and break it down into a structured data project involving specific schemas, logic, and metrics.
• AI Readiness: Proficient in leveraging AI tools for rapid prototyping of SQL logic, automating documentation, and identifying opportunities where machine learning can enhance traditional business reporting.
• Communication: Expert-level ability to navigate two worlds. You can discuss JOIN logic and latency with engineers in the morning and LTV or churn-reduction strategies with executives in the afternoon.
• Programming: Expert in SQL, Python or R for data exploration, validation and analysis; Working experience with DBT or Git or similar.
• BI Tools:: Mastery of visualization and report / dashboard building, and performance optimization; demonstrated experience in building with Tableau, Mode, PowerBI (or similar).

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