Data Engineer

Mundi; Montreal (administrative region); On-site; CAD 100,000 - 150,000; Full time

Job summary

AppDirect recherche un Ingénieur(e) de données sénior pour l’équipe Data Insights à Montréal. Vous concevrez et maintiendrez des pipelines lakehouse robustes (Snowflake + dbt) et piloterez les solutions de données qui alimentent les dashboards internes et clients.

Vous travaillerez avec les équipes engineering et produit pour transformer les exigences en modèles de données fiables et évolutifs, migrerez les anciens ETL vers des flux modernes et optimiserez les coûts tout en assurant la qualité

Qualifications

• 2+ années d’expérience sur Snowflake en production et pipelines ELT/transformations.

Responsibilities

• Concevoir et faire évoluer la plateforme lakehouse avec Snowflake/dbt et Databricks.
• Traduire les exigences produit en modèles et pipelines de données performants.
• Piloter la migration ETL vers des pipelines modernes et incrémentiels.
• Optimiser les coûts et les performances Snowflake (clustering, crédits).
• Appliquer des outils IA pour automatiser, tester et déployer les pipelines.
• Favoriser l’auto-service et l’appropriation des produits de données par les BU.

Skills

AI-assisted dev

Spec-driven development

Snowflake expertise

dbt mastery

AWS

Data governance

Collaboration & communication

Tools

Databricks

Fivetran

Cube.dev

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

About AppDirect

Become a digital, global citizen and enable the new generation of digital entrepreneurs around the world. AppDirect 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.

About the Data Insights Team

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.

About You

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.

What You’ll Do and How You’ll Make an Impact

• 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.

What we’re looking for

• AI-Assisted Development: Strong understanding of AI-assisted development workflows, with proven hands-on experience using tools such as Cursor, Claude, OpenCode, GitHub 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 experience with AWS cloud services.
• Data Governance: A solid understanding of data quality, lineage, validation techniques, and data governance.
• Collaboration & Communication: Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders, gather requirements, and work effectively in a distributed team.

Preferred / Additional Strengths

• Databricks: Hands-on Databricks experience (workspaces, jobs/workflows, Spark SQL/PySpark, Delta Lake) to contribute to lakehouse work alongside Snowflake.
• Managed Ingestion (Fivetran): Exposure to Fivetran (or similar ELT connectors) for reliable source-to-warehouse ingestion, connector governance, and schema-evolution handling.
• Semantic Layer (Cube.dev): Exposure to Cube.dev (or a similar semantic/metrics layer) for governed, self-serve analytics and consistent metrics across products and consumers.
• Real-Time Streaming: Strong preferred experience building and maintaining real-time data solutions using streaming platforms like Apache Kafka.

At AppDirect, we believe that innovation thrives in an environment that houses diversity of excellence, experience and thought. We respect each AppDirector as their own fingerprint; unique with no one alike. We foster an environment of inclusion without regard to race, religion, age, sexual orientation, or gender identity enabling AppDirectors to embrace their uniqueness to do their best work. As such, we strongly encourage applications from Indigenous peoples, racialized people, people with disabilities, people from gender and sexually diverse communities, and/or people with intersectional identities.

At AppDirect, AI tools may assist our recruitment team with administrative automations — always under human oversight. AI tools do not make hiring decisions or solely automated decisions about your candidacy – all decisions are made by our people. By submitting your application, you acknowledge that your information may be processed in this way. You may request access or deletion at any time by contacting [e-mail].