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, PlushCare, Nasty Gal) with expertise in scaling enterprises (TripAdvisor, Walmart, BARK). Featured in TechCrunch, 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
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
