Data Engineer

Dutch is transforming veterinary care by making expert treatment accessible anytime, anywhere. Our mission is simple: help every pet live their happiest, healthiest life by connecting pet parents with licensed vets through seamless virtual visits.

We’re the only veterinary telemedicine service that can diagnose, prescribe, and ship medications directly to customers in most states. For less than $100 per year, Dutch offers real relief and convenience for pets and their families.

Backed by world-class investors including Forerunner Ventures, Eclipse Ventures, and Bling Capital, our team is made up of successful startup founders (Hims, Plush Care, Nasty Gal) with expertise in scaling enterprises (Trip Advisor, Walmart, BARK). Featured in Tech Crunch, Forbes, Wired, and Axios, Dutch is setting the standard for quality, accessibility, and compassion in pet care.

We’re looking for a Lead Data/Analytics Engineer to own how Dutch measures its product and business. You’ll run the event instrumentation pipeline, build the models and metrics layers that teams use to make decisions, and sit shoulder-to-shoulder with product managers to design and analyze experiments. When data engineering work needs doing, you can pick it up without missing a beat.

This is a senior individual contributor role. You’ll work across our modern data stack:
Segment and Amplitude for behavioral data, Snowflake and dbt for warehousing and modeling, Prefect for orchestration, and Sigma for BI. You’ll partner with the BI team (which governs all data model builds) and with product engineering to make sure every dashboard, metric, and experiment runs on data the company trusts.

• Own the event pipeline from instrumentation through Segment into Amplitude, Iterable, and Snowflake, including sources, destinations, and reverse ETL
• Define and publish a typed event schema and governance workflow that frontend teams build against, so event data stays consistent across web and mobile
• Design and validate tracking plans for new features and surfaces, and confirm events flow end to end before launch
• Partner with product managers to design experiments in Amplitude: define hypotheses, select metrics, set guardrails, and size tests
• Build Amplitude charts, funnels, cohorts, and dashboards that help product teams answer their own questions without waiting on you
• Debug identity resolution, user properties, and experiment assignment issues across Segment, Amplitude, and downstream tools
• Analyze experiment results and present findings to stakeholders with clear recommendations
• Build, maintain, and optimize ELT pipelines using dbt, Prefect and Fivetran
• Own core datasets and dbt models in Snowflake in partnership with the BI and product engineering teams
• Lead infrastructure modernization: orchestration and dbt version upgrades, flow runtime reduction, Snowflake compute and storage cost optimization
• Drive warehouse security and governance work, including access controls, remediation of security assessment findings, and PII handling
• Implement data quality tests, freshness checks, observability, and alerting across critical pipelines
• Troubleshoot pipeline failures and data incidents, and drive root-cause fixes rather than patches

• Deliver ready-to-consume data marts that power product features such as recommendations and personalization, plus the baselines to measure them
• Contribute to the semantic layer that gives BI tools and AI features a single source of truth for metric definitions
• Supply reliable, well-governed data to AI features that improve the member experience and vet workflows
• Define and document the company’s core metrics so every team calculates things the same way

• 6+ years of experience in analytics engineering, data engineering, or hybrid data roles
• Strong proficiency in SQL and Python
• Deep hands-on experience with Snowflake or a comparable cloud data warehouse
• Production experience with dbt, including testing, documentation, and CI
• Experience with product analytics platforms, ideally Amplitude, including funnels, cohorts, experiment configuration, and identity resolution
• Experi…