[Hiring] Data & Analytics Engineer @Practice Better

Role Description

Ready to make a real impact on global health and wellness care? Practice Better is an all-in-one platform helping health and wellness practitioners run their businesses, care for their clients, and scale their impact.

This isn't a traditional data engineering role. We don't need someone who only knows how to build pipelines. We need someone who understands how the business works — how Stripe processes transactions, how HubSpot triggers campaigns, how churn is calculated and where the nuance lives — and uses that understanding to make the data layer trustworthy, actionable, and clear.

This is a sole-contributor role on a small, high-output team. You'll own the full stack — pipelines, data models, integrations, and the data layer underpinning our AI-assisted analytics — but your real value is in connecting the dots between systems, data, and the humans who make decisions from it.

What You’ll Be Doing

• Understand the Business Through the Data
  • Develop a deep working knowledge of how our core business systems function — Stripe, Square, HubSpot, and others.
  • Be the person who can explain why a number looks the way it does, not just where it came from.
  • Partner with stakeholders across Growth, Customer Success, Marketing, and Payments to understand data dependencies.
  • Act as a thought partner and soundboard for the Head of RevOps.
• Own the Data Stack
  • Own and evolve the full data infrastructure: Snowflake, dbt, Stitch, Rivery, and pipeline orchestration.
  • Build and maintain ELT/ETL pipelines and dbt models supporting analytics, reporting, and the AI warehouse agent.
  • Manage Snowflake for performance, cost, and reliability.
  • Build and maintain integrations between production systems and the data warehouse.
• Ensure Data Quality & Reliability
  • Implement data quality monitoring, testing frameworks, and alerting.
  • Trace anomalies to root causes and ensure leadership is making decisions on reliable data.
  • Establish and maintain data governance standards.
  • Partner with Product and Engineering to instrument event tracking.
• Advance AI-Assisted Data Workflows
  • Design and evolve AI-assisted data workflows.
  • Bring strong intuition for AI failure modes.
  • Enable stakeholders to self-serve through AI-assisted tooling.

Qualifications

• 3–5+ years in a data-focused role — data engineering, analytics engineering, BI engineering, or data science with an engineering bent.
• Experience at a small or mid-stage company where you owned the full picture.
• A genuine curiosity about business systems.
• SQL and working experience with dbt and Snowflake (or equivalent warehouse tooling).
• Proficiency for pipeline development and automation.
• Experience building and optimizing ELT/ETL pipelines at scale.
• Clear, proactive communication.
• A pragmatic approach to AI.
• Experience with version control (Git).

Requirements

• Final offers are determined by several factors, including experience, demonstrated skills, and location.
• Anticipated Base Salary Range (Canada): $135,000 - $145,000/year.

Benefits

• Comprehensive health, dental, and vision coverage from day 1.
• RRSP matching.
• Generous paid parental leave.
• Annual learning stipends.
• Unlimited vacation.
• $750 annual Health & Wellness Allowance.
• $1,000 annual Learning & Development Allowance.
• $500 annual Home Office Allowance.
• Company-wide holiday closure in December.