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Lead Data/AI Engineer

Dutch
Vancouver, BC

Quick apply

Job details

12 hours ago

Benefits

Disability insurance
Dental care
Paid time off
Vision care

Skills

CI/CD
Looker
Cloud infrastructure
Azure
Law
Git
Google Cloud Platform
Tableau
SQL
AWS
Contracts
GitHub
AI
Data warehouse
Python
Debugging

Full job description

About Us

Dutch Vet 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.

As one customer put it: “Dutch was the only site that would diagnose and prescribe meds as well as ship the meds.”

Here’s what other customers have said about Dutch Vet:

"The easiest vet visit you'll ever have.”

"More thorough than my in-person vet.”

"No nonsense, quick, easy and friendly veterinarian. Much cheaper than our regular local vet that couldn’t get us in. So glad I found Dutch!"

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.

THE ROLE:

We're looking for a Lead Data/AI Engineer to own the pipelines, event tracking, and data models that power analytics, reporting, and AI features across Dutch. This role sits at the center of 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 closely with the BI team, which governs all data model builds, and with product engineering to make sure every dashboard, metric, and product decision runs on data the company trusts.

WHAT YOU'LL DO:

Data Engineering & Infrastructure (50%)

Build, maintain, and optimize ELT pipelines using dbt, Prefect, Fivetran, and Airbyte
Own core datasets and dbt models in Snowflake in partnership with the BI and product engineering teams
Lead infrastructure modernization, including orchestration and dbt version upgrades, flow runtime reduction, and 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

Event Tracking & Product Analytics (30%)

Own the event pipeline from instrumentation through Segment into Amplitude and Snowflake, including sources, destinations, and reverse ETL
Define and publish a typed event schema and governance workflow that frontend teams implement against, so event data stays consistent across web and mobile
Design and validate tracking plans for new features and surfaces, and confirm events flow reliably end to end
Debug identity resolution, user properties, and experiment assignment issues across Segment, Amplitude, and downstream tools
Build Amplitude charts, funnels, and dashboards that help product teams answer their own questions

Analytics & AI Support (20%)

Deliver ready-to-consume data marts that power product features such as recommendations, plus the baselines to measure them
Supply reliable, well-governed data to AI features that improve the member experience and vet workflows
Contribute to the semantic layer that lets AI tools answer data questions accurately

WHAT YOU'LL BRING:

5+ years of experience in 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 customer data platforms and event pipelines, ideally Segment, including tracking plan design and destination debugging
Experience with product analytics tools, ideally Amplitude, including funnels, experiments, and identity resolution
Experience with orchestration tools such as Prefect, Airflow, or Dagster
Comfortable with Git-based workflows and CI/CD tools such as GitHub Actions
Experience working with cloud infrastructure (AWS, GCP, or Azure)
Familiarity with BI tools like Sigma, Looker, or Tableau
Bonus: experience with semantic layers, data contracts, or supporting ML and LLM applications in production