Senior Data & Insights Engineer, New Venture

At Spring Health, we’re on a mission to revolutionize mental healthcare by removing every barrier that prevents people from getting the help they need, when they need it. Our clinically validated technology, Precision Mental Healthcare, empowers us to deliver the right care at the right time—whether it’s therapy, coaching, medication, or beyond—tailored to each individual’s needs.

We proudly partner with over 450 companies, from startups to multinational Fortune 500 corporations, as a leading provider of mental health service, providing care for 10 million people. Our clients include brands you use and know like Microsoft, Target, and Delta Airlines, all of whom trust us to deliver best-in-class outcomes for their employees globally. With our innovative platform, we’ve been able to generate a net positive ROI for employers and we are the only company in our category to earn external validation of net savings for customers.

We have raised capital from prominent investors including Generation Investment, Kinnevik, Tiger Global, Northzone, RRE Ventures, and many more. Thanks to their partnership and our latest Series E Funding, our current valuation has reached $3.3 billion. We’re just getting started—join us on our journey to make mental healthcare accessible to everyone, everywhere.

Reporting to the Head of Engineering, New Venture, and partnering closely with engineering, product, and clinical teams, the Senior Data & Insights Engineer will own the end-to-end data layer, from pipelines and data models to analytics and dashboards, ensuring data is reliable, accessible, and drives decision-making across the business.

This is not a narrow pipeline-focused role, but a high-impact, high-autonomy position where you will be the go-to partner for answering critical business and product questions, ensuring data integrity, and continuously improving how data flows across systems. You will work across backend systems (Postgres), our data warehouse (Snowflake), and analytics tools (e.g., Mixpanel) to unify fragmented data into a reliable and actionable source of truth. In this early-stage environment, you will have the opportunity to define both the data architecture and how data is used day-to-day, with full ownership of the data layer and direct impact on product, clinical, and business decisions.

Please note that this is a hybrid role based in New York City, with an expectation to be in the office 2–3 days per week at our 60 Madison Avenue location. Candidates must be based in the NYC metro area or able to relocate independently within 90 days of their start date. Occasional travel will be required for team on-sites. 

• →Build and maintain data pipelines that move data from application databases (e.g., Postgres) into Snowflake.
• →Design, extend, and optimize data models across backend systems and the data warehouse.
• →Ensure data reliability, integrity, and timeliness across all systems and reporting layers.
• →Translate ambiguous business and product questions into clear analyses, dashboards, and SQL queries.
• →Develop dashboards and self-serve analytics tools for product, clinical, and operations teams.
• →Identify and resolve data discrepancies across systems (e.g., backend, warehouse, analytics tools).
• →Integrate and reconcile multiple data sources into a consistent and trusted source of truth.
• →Partner cross-functionally to define metrics, improve data accessibility, and drive data-informed decisions.
• →Evaluate and implement tools for data orchestration, transformation, and scaling the data platform.
• →Continuously improve data architecture to support a transition from scrappy workflows to scalable systems.

• The team trusts data and uses it daily for decision-making
• Key metrics are clearly defined, consistent, and easy to access
• Data discrepancies are proactively identified and resolved
• New data questions can be answered quickly without reinventing pipelines
• Dashboards and reporting tools are widely adopted and reduce reliance on ad hoc requests.

• 5+ years of experience in data engineering, analytics engineering, or similar roles
• Strong SQL skills (Snowflake or similar data warehouse experience required)
• Experience working with backend systems (Python, Postgres or similar)
• Proven ability to build and maintain data pipelines (ELT/ETL)
• Experience working with product analytics tools (e.g., Mixpanel, Amplitude)
• Strong intuition for data quality and debugging inconsistencies across systems
• Ability to turn ambiguous questions into structured analysis and insights
• Comfortable operating in a high-autonomy, fast-moving environment

• Experience with tools like dbt, Airflow, Dagster, or similar
• Experience designing event tracking systems
• Exposure to healthcare or regulated data environments
• Experience building a data stack from early stage to scale

The target base salary range for this position is $159,100 - $196,480, and is part of a competitive total rewards package including equity and benefits. Individual pay may vary from the target range and is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all employee pay and compensation programs annually using Radford Global Compensation Database at minimum to ensure competitive and fair pay.