Remitly · Bangalore, IndiaPrepare for this interview
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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 Senior Manager, Analytics at Remitly is a multi-disciplinary leader responsible for directing a team of Analysts, BI Specialists, Data Scientists, and Data Engineers. You will oversee the end-to-end data and analytics lifecycle - define business requirements, design 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 and machine learning models. This role is based in our Bangalore office and reports to the Director of Analytics. You Will: Team Leadership & People Management : Select, develop, and evaluate a diverse team of BI specialists, 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 and models 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. You Have: 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.
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