Lead Data/Analytics Engineer

Résumé du poste

The Lead Data/Analytics Engineer will own the event instrumentation pipeline, build data models, and partner with product managers to design and analyze experiments. They will also manage ELT pipelines, optimize data infrastructure, and define core company metrics to ensure data trust and consistency.

Détails du poste

About Us 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. The Role 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. \n WHAT YOU'LL DO: Product Analytics & Experimentation (40%) 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 Data Engineering & Infrastructure (35%) 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 Metrics, Semantic Layer & AI Data Products (25%) 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 WHAT YOU'LL BRING: 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) WHY YOU'RE A GREAT FIT: 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 WHY WORK FOR DUTCH? 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! DUTCH'S GUIDING PRINCIPLES Pets First – business and medical decisions are always guided by the pet’s best interest. We’ll never compromise on pet health and we’re all here because we care about their well-being Agile Like a Cat – We have a bias toward swift action, while maintaining quality and accuracy. For us, that means being able to turn on a dime, like a cat, analyze our options – even ones that may not be on the table – then execute without perfection getting in the way Creativity is our Catnip – Creativity feeds us and helps us push boundaries to always find better solutions, making the complex more accessible and easier to understand Be the Human Your Dog Thinks You Are – Be kind, show care for your colleagues, and even if you’re an expert - give others context, reinforce the positive, and help them understand. \n

Ce que vous ferez

The Lead Data/Analytics Engineer will own the event instrumentation pipeline, build data models, and partner with product managers to design and analyze experiments. They will also manage ELT pipelines, optimize data infrastructure, and define core company metrics to ensure data trust and consistency.

Exigences

Candidates must have 6+ years of experience in analytics or data engineering with strong proficiency in SQL and Python. Deep hands-on experience with Snowflake, dbt, and product analytics platforms like Amplitude is required.

Avantages

• Health Insurance • Dental Insurance • Vision Insurance • Life Insurance • Disability Insurance • Flexible PTO • Mental Wellbeing Options • Robust Holiday Schedule • Registered Retirement Savings Plan • Growth Opportunities

Compétences indiquées

• SQL · Souhaitée
• CI/CD · Souhaitée
• Git · Souhaitée
• Python · Souhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• SQL
• Python
• Snowflake
• dbt
• Amplitude
• Segment
• Data Engineering
• Product Analytics
• A/B Testing
• Prefect
• Data Modeling
• Git
• CI/CD
• Data Governance
• ETL/ELT
• Metrics Definition
• SQL (Programming Language)
• Data Analysis
• Business Intelligence
• Extract Transform Load (ETL)
• Dashboard
• Agile Methodology
• Data Warehousing
• Management
• Governance
• Troubleshooting (Problem Solving)
• Workflow Management
• Self-Discipline
• Pipelines
• Machine Learning
• Snowflake (Data Warehouse)
• Amazon Web Services
• Warehousing
• Apache Airflow
• Artificial Intelligence
• Data Quality
• Cloud Infrastructure
• Python (Programming Language)
• Microsoft Azure
• Creativity
• Observability
• Debugging
• Front End Design
• Compassion
• Product Engineering
• Tableau (Business Intelligence Software)
• Telehealth
• Github
• Git (Version Control System)
• Experimentation

Domaines d’emploi

• Data & Analytics
• Software
• Engineering
• Technology
• Healthcare
• Data Analytics Engineer
• Data Analyst
• Statistical, Mathematical and Related Associate Professionals
• Business Intelligence Analysts
• Data Scientists