Analytics Engineer

Tandem
New York officePosted 14 August 2025

Job Description

Why you should join usTandem is a generational opportunity to rethink how we bring new therapies to market, and our path to doing so is significantly de-risked – we have:Exponential organic growth: We have product-market fit and are growing rapidly through word-of-mouth. Tandem supports thousands of patients every day, is doubling doctor users every quarter, and is working with the largest biopharma companies in the world.An AI-first business model: Our approach is distinctly enabled by AI, but our business will get stronger (not commoditized) as foundation models improve. We are building durability through two-sided network effects that will compound over time.Top tier investors: With the traction to support conviction in our model, we raised significant funding from investors (including Thrive Capital, General Catalyst, Bain Capital Ventures, and Pear VC) to build an exceptional team of engineers and operators.Our number one priority is scaling to market demand. We are looking for individuals who are high horsepower, high throughput, and hyper resourceful to help us increase capacity and grow. We move fast and need to move faster.All full-time roles are in person in New York. You can learn more about working with us in the last section of this page.About the roleAs an Analytics Engineer at Tandem, you’ll build the data foundation that powers how we operate, measure, and grow. You’ll design and maintain our core data models, pipelines, and reporting infrastructure — ensuring the right people have access to clean, trustworthy, decision-grade data at the speed we need to move. This is a cross-functional, impact-heavy role where you’ll work closely with product, ops, growth, and leadership to build the systems that enable better, faster decisions across the company.You’ll also help define our analytics engineering practices: how we structure metrics, review code, manage pipelines, and build for scale. Your work will directly support everything from product usage visibility to operational performance to life sciences client reporting.This is a demanding role, with a high level of autonomy and responsibility. You will be expected to "act like an owner" and commit yourself to Tandem's success. If you are low-ego, hungry to learn, and excited about intense, impactful work that drives both company growth and accelerated career progression, we want to hear from you.If you join, you will:Build and maintain the core data models that serve as the foundation for internal analytics and client-facing insightsDesign and operate the data pipelines that transform raw sources into clean, analytics-ready tablesCreate dashboards and reporting tools that drive performance visibility and decision-making across product, ops, and GTMDefine and enforce metric consistency across teams — including core business KPIs and product usage definitionsHelp improve and scale our analytics stack (we use GCP BigQuery and Dataform, Fivetran, Postgres, and dashboarding tools)Collaborate with stakeholders across teams to understand data needs and translate them into reliable systemsContribute to internal data culture through documentation, education, and code quality standardsWe’re looking for you if you have:3–6 years of experience in analytics engineering, data engineering, or a technical data analyst role with production ownershipExpert-level SQL and comfort working in a code-first environment (versioning, testing, documentation)Experience designing data models that balance usability, performance, and long-term maintainabilityFamiliarity with the modern data stack — dbt, Fivetran, Airflow, GCP/AWS/Snowflake, Metabase (or equivalents)Strong written and verbal communication that allows you to be an effective participant in both internal debates and external relationshipsTrack record of moving quickly, finding shortcuts, and going to unreasonable lengths to deliver on goalsHigh NPS with your former teammatesThis is a list of ideal qualifications for this position. I ... (truncated, view full listing at source)
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