Senior Manager of Compliance Analytics & Business Intelligence Job Burnaby area,BC Canada,IT/Tech

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
The Sr Manager, Compliance Analytics & BI at Remitly is a multi-disciplinary leader responsible for directing a team of Analysts and Data Engineers
You will oversee the end-to-end data and analytics lifecycle - define the data pipelines, drive and influence the architecture of data marts, and deliver mission‑critical and actionable analytics products
This role requires you to balance tactical and hands‑on technical expertise with strategic thinking and leadership to ensure that our data and analytics infrastructure directly enable impactful business decisions and production‑grade analytics
Team Leadership & People Management:
Select, develop, and evaluate a diverse team of data scientists and analytics professionals, providing mentorship on both technical craft and professional growth
Data Engineering Oversight:
Direct the engineering team in building and operating reliable, scalable data pipelines (ETL/ELT) that ingest data from diverse sources and make it available for broader consumption, at scale
Data Architecture & Mart Modeling:
Lead the design and implementation of domain‑specific data marts, ensuring data structures are optimized for both descriptive metrics and advanced statistical modeling
Strategic Advisory:
Advise business leaders by providing data‑based strategic direction and identifying opportunities that impact company‑level OKRs
Operational Excellence:
Manage objective‑based assignments, determine resource allocation (balancing technical debt with new features), and establish procedures for well‑tested, documented, and scalable code
Stakeholder

Collaboration:

Partner with Engineering, Product, and other Business functions to ensure data integrity and real‑time availability, where needed

Benefits

Spend up to $1,000 per year on costs related to continuing education or on travel to countries Remitly serves, allowing you to gain insights to our customer’s journeys
All of our office spaces offer our employees a place to collaborate and celebrate. With locally sourced artwork and vibrant designs, they create an environment that all can enjoy
Fill your cup up outside of work and take advantage of our generous paid time off policies, leave policies, and flex working hours to ensure you are able to meet the demands of life outside of work
Tap into the learning routines, resources and affinity groups Remitly provides to help you further your own DEI journey
Contribute to the communities we serve through volunteering, employee giving, or civic advocacy
Remitly provides rich benefit plans intended to cover the needs of our diverse teammates

Analytics Toolkit:
Mastery of SQL and Python/R for data transformation and analysis
Communication:
Exceptional ability to translate technical infrastructure needs and complex data insights into clear narratives for executive stakeholders
Platforms:
Familiarity with AWS Services (Sagemaker, S3, Glue), visualization tools (Tableau, Mode), and experimentation platforms
Experience:

Extensive experience (8-12+ years) in data engineering, data science, or analytics roles. Proven experience managing technical professionals and guiding teams through complex, abstract problem spaces
Problem Solving: A “master of the 80/20 rule” who can triage complex challenges toward the most effective engineering or analytical methodology
Educational Background:
Typically requires a Bachelor’s degree in a quantitative field (e.g., Computer Science, Engineering, Statistics), with a Master’s or PhD preferred for deep data science oversight
Data Modeling:
Expertise in designing scalable data architectures and system designs
AI Readiness:
Demonstrated familiarity in using AI tools such as Claude, Gemini, and/or ChatGPT to accelerate problem‑solving, automate routine data tasks, and generate insights for complex business problems
Data Engineering:
Deep knowledge of data ingestion methods, pipeline orchestration (e.g., Airflow), and database technologies

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