Senior Analytics Engineer

Company Overview

Mantra Health is an award-winning digital mental health provider on a mission to make evidence-based care more accessible to students. We partner with colleges and universities to offer comprehensive virtual mental health services, including therapy, psychiatry, 24/7 crisis care, emotional wellness coaching, and self-care content.

Our technology solutions seamlessly integrate with campus health systems to enhance student well-being and improve graduation rates. Recognized as a leader in digital mental health, Mantra Health was named a Rising Star by the UCSF Digital Health Awards and won Juniper Research’s Gold Star for Best Digital Therapeutic Solution. Today, our programs support over one million students across 150 campuses, including Penn State, MIT, and Miami Dade College. 

We’ve raised over $34m from leading investors. We’re looking for ambitious, talented, action-oriented individuals to join us in shaping the future of student mental healthcare.

Opportunity for Impact

We are seeking an experienced Sr Analytics Engineer to play a pivotal role in enhancing and scaling the data foundation that powers meaningful insights for student mental health across Mantra Health. This is a unique opportunity to blend technical expertise with genuine human impact. You'll partner closely with stakeholders across our business to understand the real challenges students face, refine data-driven mental health solutions, and create measurable positive outcomes for our partners. By designing thoughtful data pipelines, warehousing models, and analytics frameworks, you'll help transform diverse data sources (including sensitive student information under HIPAA/FERPA/SOC2 compliance) into insights that drive better care decisions and support student wellbeing. This role is for someone who thrives in navigating complex data challenges, refining analytics architecture, and using data to make a tangible difference in students' lives.

As a key member of our engineering team within a mission-driven edtech startup, you'll collaborate closely with product, engineering, and operational teams. You will leverage a modern data stack (Snowflake, DBT, Looker) to establish robust, scalable data infrastructure, directly influencing our ability to innovate on projects related to understanding drivers of student well-being, reducing dropout rates, and delivering compelling population health reports. This position offers significant ownership, the chance to shape our evolving data practices, and high visibility within a dynamic environment committed to improving student mental health.

What You’ll Do

• Build & Manage Data Pipelines: Design, implement, monitor, and maintain scalable and reliable ELT pipelines using modern tooling, ingesting data from diverse sources including APIs, flat files, and databases like PostgreSQL.
• Design & Implement Data Warehouse Models: Architect, develop, and refine robust data models within Snowflake (staging, unified models, data marts) using DBT, optimizing for analytical performance, clarity, and reusability.
• Drive Actionable Insights: Proactively partner with Product, Clinical, and other stakeholders to translate ambiguous business problems into analytical questions; conduct exploratory analysis to uncover insights; build and communicate compelling data narratives to drive decisions.
• Champion Data Quality & Engineering Practices: Implement rigorous data quality testing (e.g., DBT tests), monitoring, and validation; drive SDLC best practices (version control via Git, CI/CD via GitHub Actions/CircleCI) for all analytics code; ensure all data processes adhere to strict security and compliance standards (HIPAA/FERPA/SOC2); maintain clear documentation.

Who You Are 

• Experienced Analytics Engineer: You bring 5-8 years of dedicated experience building and managing data pipelines, warehouses, and analytics solutions, with a proven track record in cloud environments (Snowflake strongly preferred) and startups.
• Modern Data Stack Expert: You possess deep SQL proficiency, strong Python skills for data tasks, mastery of DBT (Cloud or Core) development and best practices, and significant experience enabling analytics with BI tools (Looker preferred).
• Skilled Data Modeler: You are proficient in data modeling techniques (e.g., dimensional modeling, normalization) and can translate complex business requirements into effective, scalable data warehouse structures.
• Collaborative Problem Solver: You excel at analyzing complex data challenges, clearly communicating technical concepts to diverse audiences, and working cross-functio