Analytics Engineer

Remitly is a company focused on providing secure and reliable financial services for global customers. They are seeking an Analytics Engineer to lead data engineering initiatives that support their Non-Fraud Loss program, enabling loss detection and reduction across various products and regions.

Responsibilities:

• Design and build reliable, scalable ETL pipelines and unified data workflows, including automated tagging, reporting logic, and core semantic-layer infrastructure
• Architect dimensional data models that support self-service analytics, ensure consistency across datasets, and scale with evolving business needs
• Develop end-to-end analytics and dashboard solutions, from backend data transformations to intuitive front-end visualizations, using tools such as Tableau or Mode and applying strong UX best practices
• Ensure data integrity, performance, and governance across BI assets through structured testing, documentation, and quality-assurance processes
• Expand analytics and reporting capabilities to new products and program requirements by collaborating with cross-functional teams to design and refine reporting logic
• Support and train business users to strengthen data fluency, encourage BI tool adoption, and promote effective use of analytics products

Requirements:

• Position requires a Master's degree in Data Science, Business Analytics, Information Systems, or a related quantitative or computing field, and 3 years of experience with business interface development, end-to-end analytics engineering, and quantitative product data analysis
• 3 years of experience with using SQL to design performant, reusable data models
• 3 years of experience with designing and implementing scalable data pipelines and reporting systems for high-volume, business-critical use cases, including automation of tagging and reporting logic
• 3 years of experience with applying product-level data analysis to reduce operational lift and enable real-time monitoring at scale
• 3 years of experience with delivering actionable insights to leadership through intuitive, scalable dashboards, including optimization of dashboard performance
• 3 years of experience with utilizing BI and analytics tools including AWS Redshift, AWS QuickSight, AWS SageMaker, AWS Glue, Git, PowerBI, Tableau
• 3 years of experience with conducting A/B testing and causal inference analysis
• 3 years of experience with working with big-data and programming tools such as Hadoop, Hive, Java, Python (including Scikit-Learn and SciPy), Spark, and R to build machine-learning or advanced analytical solutions