Dutch · Vancouver
Data & AIDataHybridposted 4w ago
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
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
Experience with customer data platforms and event pipelines, ideally Segment, including tracking plan design, destination management, and debugging
Demonstrated experience designing and analyzing A/B tests or product experiments
Experience with orchestration tools such as Prefect, Airflow, or Dagster
Comfortable with Git-based workflows and CI/CD tools such as GitHub Actions
Uses AI tools (code assistants, LLMs, etc.) as part of daily work and can show how
Familiarity with BI tools like Sigma, Looker, or Tableau
Bonus: experience with semantic layers, data contracts, ML/LLM applications in production, or cloud infrastructure (AWS, GCP, or Azure)
You treat trust in the numbers as the product. When a metric is wrong, you feel it personally
You can build an event taxonomy from scratch and also explain to a PM why their experiment needs a bigger sample size
You’re as comfortable writing dbt models as you are reviewing an experiment readout with a product lead
You use AI tools every day to move faster and expect to keep pushing that boundary
You’re self-directed and comfortable managing your own priorities in a fast-moving environment
You care about data quality, reproducibility, and documentation because you’ve been burned by their absence
You love animals
Competitive salary range between $185K - $220K CAD
Hybrid working location
Health, Dental and Vision Insurance
Life and Disability Insurance
Flexible PTO
Mental Wellbeing Options
Robust Holiday Schedule
Registered Retirement Savings Plan
Growth Opportunities!