Senior Manager Compliance Analytics & BI

Remitly•Burnaby, BC

1d•CA$148,000 - CA$185,000•Hybrid

About The Position

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.

Requirements

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.
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.
Data Modeling: Expertise in designing scalable data architectures and system designs.
Analytics Toolkit: Mastery of SQL and Python/R for data transformation and analysis.
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.
Communication: Exceptional ability to translate technical infrastructure needs and complex data insights into clear narratives for executive stakeholders.

Responsibilities

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.