Data Engineer

About the Role

We are seeking a Data Engineer who thrives at the intersection of data, product, and engineering. In this role, you’ll play a critical part in improving how we track user behaviour, structure our data, and turn raw information into clear, actionable insights.

This position is ideal for someone with a strong technical foundation—particularly in SQL and event-tracking systems—who also understands product thinking and business context. You’ll be working closely with product managers, engineers, and marketing teams to shape the way we define and measure success.

Key Responsibilities

Audit and improve event-tracking implementations, data layer structure, and naming conventions
Design and manage data models, dashboards, and reporting infrastructure in Metabase
Build and maintain operational and analytical dashboards used by cross-functional teams
Analyze product usage, customer behavior, funnels, and retention metrics to inform decision-making
Collaborate with product and engineering teams to define key metrics and ensure tracking accuracy
Document data schemas, definitions, and KPI logic to ensure shared understanding across teams
Enable a self-serve data culture by building helpful tools, alerts, and guidance for non-technical stakeholders


Requirements

3–5 years of experience in analytics, BI, or data roles
Advanced proficiency in SQL (preferably in PostgreSQL or MySQL)
Hands-on experience with Metabase, including data modeling, dashboard design, alerts, and dynamic filters
Strong understanding of event-based analytics and behavioral data structures
Ability to translate business problems into structured analyses and clear recommendations
Experience documenting and communicating tracking specifications and data definitions


Nice to Have

Familiarity with event tracking tools such as Segment, PostHog, or Snowplow
Scripting experience in Python or JavaScript for ad-hoc data tasks
Background in SaaS, marketplaces, or high-growth digital products
Experience with retention analysis, funnel modeling, and cohort tracking
Proficiency in Excel/Google Sheets for complementary modeling and analysis