Senior Data Engineer

Job Description

Pour la version française de cette description de poste, veuillez consulter le lien suivant / For the French version of this job description, please refer to the following link:

• Ingénieur(e) de données sénior

Become a digital, global citizen and enable the new generation of digital entrepreneurs around the world. App Direct offers a subscription commerce platform to sell any product, through any channel, on any device - as a service. We power millions of subscriptions worldwide for organizations. We do this by our values-driven culture—one that enables you to Be Seen, Be Yourself, and Do Your Best Work.

Our mission is to unify data from every business unit into a governed lakehouse and semantic layer, powering analytics, AI, reports, data sharing, and both internal and customer-facing dashboards.

We’re hiring a Senior Data Engineer for Data Insights in Montreal—someone with a Data as a Product mindset who builds production pipelines and models others can trust and reuse.

You’ll build production data products and lakehouse pipelines that power analytics and both internal and customer-facing dashboards—partnering across engineering and product, establishing clear data contracts, and leaving patterns others can reuse.

• Platform Architecture & Modeling:
  Design, build, and evolve the lakehouse data platform—reusable models and pipelines on Snowflake + dbt, with Databricks workloads where they fit—so analytics and product teams get reliable, governed data products.
• Requirements & Stakeholder Partnership:
  Translate product and business requirements into data models and pipelines—working with PMs, BUs, and engineers so domain logic lands correctly in production.
• Pipeline Modernization:
  Migrate legacy ETL processes to modern, efficient streaming and incremental pipelines, choosing Snowflake or Databricks based on fit.
• Snowflake Performance & Cost:
  Operate and tune Snowflake for reliability and efficiency—warehouse sizing and utilization, clustering/partitioning where it pays off, and visibility into credit spend so scale doesn’t mean runaway cost.
• AI-Assisted Operations:
  Apply AI-assisted development tools and spec-driven workflows to design, automate, and ship data pipelines and platform.
• Self-Service Enablement:
  Facilitate scoped data onboarding and empower business unit engineers to build their own data products on top of our platform.
• Customer-Facing Data Products:
  Build and evolve data behind customer-facing products—including the reporting service and App Insights—so pipelines and models deliver trustworthy product experiences.
• Data Quality & Trust:
  Ensure data quality by driving and implementing robust data governance, automated testing, validation techniques, and lineage.
• Metadata Management:
  Curate rich metadata in Unity Catalog and Snowflake to power downstream consumption, including AI agents and our semantic layer (Cube.dev).
• Research & Innovation:
  Research solutions to complex problems and lead proof-of-concepts to evaluate emerging technologies.
• Documentation & Culture:
  Author and maintain high-quality documentation to support knowledge sharing and AI-assisted workflows.

• AI-Assisted Development:
  Strong understanding of AI-assisted development workflows, with proven hands-on experience using tools such as Cursor, Claude, Open Code, Git Hub Copilot, or ChatGPT to improve efficiency, automation, and code quality.
• Spec-Driven Development:
  Experience with spec-driven development: turning requirements into clear specs/plans and acceptance criteria, then implementing them (including AI-agent-assisted workflows).
• Snowflake Expertise (core skillset): 2+ years building and operating production data pipelines and models on Snowflake using SQL, Python, and dbt—shipping reliable ELT/transformations, owning quality and performance in production.
• dbt Mastery: 2+ years of hands-on experience building modular, version-controlled, and tested data models using dbt (data build tool), treating transformation as software engineering (Git workflows, code review, automated tests).
• AWS: 2+ years of…