Job description

Pelago is the leading specialty substance use care provider, built on the belief that effective treatment means matching care intensity to what each member actually needs rather than defaulting to the most expensive intervention. Our programs guide members through every stage of the substance use spectrum, from unhealthy habits to active use disorders, delivering personalized treatment for tobacco, alcohol, opioid, cannabis, and stimulant use based on individual health, habits, genetics, and goals. With Sona, our voice-first AI Mental Health Specialist, Pelago now applies that same clinically-driven model to mental health, pairing deep clinical expertise with technology to expand access without compromising care quality. We believe technology should make clinical care more precise and more human, not replace the judgment behind it. Pelago has scaled to helping hundreds of employers and health plans and has already helped more than 750,000 members better manage their substance use. If you're passionate about AI and making an impact on the health of others, join us and make it happen! About Our Data Team: Our Data team sits at the center of how Pelago makes decisions. As we scale, we're building a data function that doesn't just report on the business — it shapes it. We transform complex healthcare and product data into clean, reliable, well-documented models that power reporting, experimentation, AI initiatives, and day-to-day decision-making across the company. The Senior Analytics Engineer is a key force multiplier on that mission. Overview of the Role: We’re hiring an Analytics Engineer who loves building scalable data models, thinking deeply about business logic, and creating reusable data assets. In this role, you’ll help shape how data is structured and defined across Pelago—ensuring consistency, quality, and usability for everything from dashboards to experimentation to future machine learning use cases. This is a business intelligence role with an analytics engineering toolkit. Reporting to our Director of Analytics, you'll partner with our Commercial, Marketing, and Health Services teams to understand what they need, and then own the dbt and semantic layers that deliver it. We want someone who asks why a number looks the way it does and stays with a problem until it's actually solved. What You'll Do: Build and maintain dbt models in Redshift, designed from the business need backward rather than from the raw data forward. Apply software engineering practices to our transformation layer: DRY code, meaningful tests, clear lineage, and documentation. Turn ambiguous questions from our Commercial, Marketing, and Health Services teams into reusable data models and dashboards, built for both analysts and AI. Define and govern consistent metrics through our semantic layer, and keep testing whether they're still the right way to look at the business. Support experimentation and campaign measurement so we know what's working and why. Partner with Data Engineering and Product to understand source data, and with analytics peers to deliver analysis-ready data. Build reusable AI-driven workflows that change how the data team works. Find and fix problems in the data before they become problems in the business. The Background We Are Looking For: 5+ years in analytics engineering, BI, data analytics, or data modeling. Expert SQL and fluency with dbt, Git, and the full analytics development lifecycle, with software engineering discipline: DRY code, meaningful tests, and clear lineage. Strong data modeling and warehousing fundamentals, including clean, well-documented tables with clear grain that work for both analysts and AI. Experience building and governing metric definitions through a semantic layer, in partnership with analysts, data engineers, and product teams. A track record of turning business needs into models and dashboards that stakeholders actually use. Hands-on experience building AI-driven workflows or skills. Comfort operating autonomously while things change. Nice to Have: Experience with Cube, Looker, or similar semantic-layer and BI tools. A background in healthcare or other regulated data. Experience measuring marketing campaigns, experiments, or engagement. What you’ll love about us: We have a whole host of perks for our people! From life essentials to nice-to-haves, there are more than a few good reasons to love working with us. We strive to ensure Pelago employees have equitable access to healthcare, wellbeing, time away, and then some. Generous and meaningful equity package Full Medical, Dental, & Vision coverage 401k Plan Unlimited PTO Policy, 10 paid holidays, & company wide “Me Time” Days Paid maternity, paternity & new parent leave Flexible working environment Annual Learning and Development stipend to support continued learning and career development Wellness Reimbursement Program Access to Reproductive & Family Planning Care Substance Use Support for employees and family members At this time, we are unable to offer visa sponsorship for this position. The provided range reflects our US target salary range for this full-time position, which is part of our broader total compensation package, including incentive bonus program, stock options, comprehensive benefits, and incentive pay applicable to eligible roles. Individual pay within the range will vary based on a variety of factors like role-related experience and education, internal pay equity, and other relevant business factors. At Pelago, we are committed to an equitable and fair pay philosophy and review total compensation for our employees at least twice a year. Base Pay Range $165,000 — $185,000 USD

Requirements

Must-haves

Our Data team sits at the center of how Pelago makes decisions. As we scale, we're building a data function that doesn't just report on the business — it shapes it.
Build and maintain dbt models in Redshift, designed from the business need backward rather than from the raw data forward.
Apply software engineering practices to our transformation layer: DRY code, meaningful tests, clear lineage, and documentation.
Turn ambiguous questions from our Commercial, Marketing, and Health Services teams into reusable data models and dashboards, built for both analysts and AI.
Define and govern consistent metrics through our semantic layer, and keep testing whether they're still the right way to look at the business.
Support experimentation and campaign measurement so we know what's working and why.
Partner with Data Engineering and Product to understand source data, and with analytics peers to deliver analysis-ready data.
Build reusable AI-driven workflows that change how the data team works.
Find and fix problems in the data before they become problems in the business.
5+ years in analytics engineering, BI, data analytics, or data modeling.
Expert SQL and fluency with dbt, Git, and the full analytics development lifecycle, with software engineering discipline: DRY code, meaningful tests, and clear lineage.
Strong data modeling and warehousing fundamentals, including clean, well-documented tables with clear grain that work for both analysts and AI.
Experience building and governing metric definitions through a semantic layer, in partnership with analysts, data engineers, and product teams.
A track record of turning business needs into models and dashboards that stakeholders actually use.
Hands-on experience building AI-driven workflows or skills.
Comfort operating autonomously while things change.
Paid maternity, paternity & new parent leave
Flexible working environment
Annual Learning and Development stipend to support continued learning and career development
Wellness Reimbursement Program
Access to Reproductive & Family Planning Care

Nice-to-haves

Experience with Cube, Looker, or similar semantic-layer and BI tools.
A background in healthcare or other regulated data.
Experience measuring marketing campaigns, experiments, or engagement.

Application prep

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Keywords to mirror

aimachine learningsql

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Pto

Wellness