Sr. Analytics Engineer

Description

The company is a specialty provider of substance use care. Its programs cover the full range from unhealthy habits to active use disorders, with personalized treatment for tobacco, alcohol, opioid, cannabis, and stimulant use based on each person's health, habits, genetics, and goals.

The company has recently added a voice-first AI mental health specialist that applies the same clinical approach to mental health, aiming to widen access without lowering care quality.

The company works with hundreds of employers and health plans and has helped more than 750,000 members manage their substance use.

The Data team shapes how the company makes decisions by turning complex healthcare and product data into clean, documented models used for reporting, experiments, AI work, and daily choices. This role reports to the Director of Analytics.

Responsibilities

• Design and maintain dbt models in Redshift, starting from what the business needs and working back to the raw data.
• Bring software engineering discipline to the transformation layer: reusable code, useful tests, clear lineage, and good documentation.
• Convert open-ended questions from Commercial, Marketing, and Health Services into reusable models and dashboards that serve both analysts and AI.
• Own the dbt and semantic layers, defining and governing consistent metrics, and regularly check that those metrics still reflect the business well.
• Support experiments and campaign measurement so the company can see what works and why.
• Work with Data Engineering and Product to understand source data, and with analytics colleagues to supply analysis-ready data.
• Build reusable AI-driven workflows that improve how the data team operates.
• Spot and resolve data issues before they affect the business.

Requirements

• 5+ years of experience across analytics engineering, business intelligence, and modeling data for analysis.
• Expert SQL, and fluency with dbt, Git, and the full analytics development lifecycle, applied with software engineering discipline.
• Solid grounding in data modeling and warehousing, producing well-documented tables with clear grain that work for analysts and AI alike.
• Experience defining and governing metrics through a semantic layer, working with analysts, data engineers, and product teams.
• A record of turning business needs into models and dashboards that stakeholders use.
• Hands-on experience building AI-driven workflows or skills.
• Comfort working independently while conditions shift.
• Experience with Cube, Looker, or similar semantic-layer and BI tools.
• Background in healthcare or other regulated data.
• Experience measuring marketing campaigns, experiments, or engagement.

Conditions

The US target base salary for this full-time role is $165,000 to $185,000 USD.

Individual pay depends on factors such as experience, education, internal pay equity, and other business considerations.

Total compensation is reviewed at least twice a year.

Visa sponsorship is not offered for this position.

Benefits

• A generous, meaningful equity package, including stock options.
• Incentive bonus program, and incentive pay for eligible roles.
• Full medical, dental, and vision coverage.
• 401(k) plan.
• Unlimited PTO, 10 paid holidays, and company-wide 'Me Time' days.
• Paid leave for maternity, paternity, and new parents.
• Flexible working environment.
• Annual stipend for learning and development.
• Wellness reimbursement program.
• Access to reproductive and family planning care.
• Substance use support for employees and family members.