Analytics Engineer II, Identity

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.

Spring Health is growing our Analytics Engineering team. Analytics Engineering at Spring sits within the Business Intelligence organization and owns core reporting infrastructure used by all downstream data scientists and data analysts. In this role you will focus on building robust models, ensuring consistency across the models we build for the business, and creating documentation that enables downstream teams to access, understand, and use data effectively. You will also provide data analyses in support of larger strategic initiatives, particularly in the design and implementation stage, to ensure that new features are built in a way that supports accurate reporting, sustainability, and maintainability. Success will require you to collaborate closely with cross-functional teams to understand their data needs, and translate them into data models and reporting solutions that serve those needs.

• →Develop and maintain core data models in dbt to support key business metrics and ensure data consistency.
• →Collaborate closely with engineers on the Identity pod and your manager to define critical business metrics and ensure proper data infrastructure and reporting solutions to serve them.
• →Ensure downstream teams can access and utilize data effectively by providing comprehensive documentation and support.
• →Collaborate with other analytics engineers to ensure we’re providing consistent data across the entire organization.
• →Assist with data quality initiatives by building monitoring systems and creating processes that guarantee accurate, auditable data.
• →Regularly audit and review data models to maintain their relevance and accuracy, ensuring long-term data integrity across the organization.

• Downstream teams consistently rate their access to high-quality data as excellent, with clear documentation that allows them to find and use the data confidently and effectively.
• The data models you build provide answers to critical business questions that are consistent across the organization
• The models you build are highly performant; they contribute to a positive experience in dbt and continue to drive down cloud data costs.

• You are passionate about changing the face of mental health care and Spring Health’s mission to remove all barriers to mental health resonates with you.
• You have 3+ years of working experience working with data, with a focus on data pipeline tools.
• You are proficient with SQL and have solid experience working with modern data transformation tools, such as dbt or similar, to create and manage scalable data models.
• You have experience building and maintaining data pipelines in cloud-based environments such as Snowflake, Redshift, or BigQuery, ensuring data is easily accessible and reliable.
• You have an interest in working with data scientists and machine learning engineers to support reporting on model performance and contribute to feature engineering work.
• You enjoy digging into data discrepancies or issues to determine and fix root causes, ensuring high standards of data integrity across the organization.
• You work with data quality best practices in mind, including designing systems that ensure accuracy, consistency, and auditability of key business metrics.
• You focus on impact, finding the things you can deliver that deliver the most value for your stakeholders
• You have hands-on experience with data visualization tools (e.g., Looker, Tableau, Hex) to build or support self-serve dashboards that empower less technical teams.
• You are humble, highly motivated, and thrive in fast-paced environments
• You have a proven ability to proactively manage your own priorities and dependencies in alignment with cross-functional dependencies and product/business impact

The target base salary range for this position is $120,000 - $140,000, and is part of a competitive total rewards package including stock options 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.