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AppDirect is hiring a Senior Data Engineer for its Data Insights team in Montreal. The team's 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.
In this role, you will design, build, and evolve a production data platform on Snowflake and Databricks using dbt, creating reusable models and pipelines that analytics and product teams can trust. You'll translate product and business requirements into data models and pipelines, working closely with product managers, business units, and engineers to ensure domain logic lands correctly in production.
Key responsibilities include:
- Platform Architecture & Modeling: Design and evolve the lakehouse data platform with reusable models and pipelines on Snowflake + dbt, with Databricks workloads where appropriate.
- Requirements & Stakeholder Partnership: Translate requirements into data models and pipelines, partnering across product, business units, and engineering teams.
- Pipeline Modernization: Migrate legacy ETL processes to modern, efficient streaming and incremental pipelines.
- Snowflake Performance & Cost: Operate and tune Snowflake for reliability and efficiency, managing warehouse sizing, clustering, partitioning, and credit spend visibility.
- AI-Assisted Operations: Apply AI-assisted development tools and spec-driven workflows to design, automate, and ship data pipelines.
- Self-Service Enablement: Facilitate data onboarding and empower business unit engineers to build their own data products on the platform.
- Customer-Facing Data Products: Build and evolve data behind customer-facing products including the reporting service and App Insights.
- Data Quality & Trust: Drive 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 semantic layers.
- Research & Innovation: Research solutions to complex problems and lead proof-of-concepts for emerging technologies.
- Documentation & Culture: Author and maintain high-quality documentation to support knowledge sharing and AI-assisted workflows.
Required qualifications:
- 2+ years building and operating production data pipelines and models on Snowflake using SQL, Python, and dbt.
- 2+ years of hands-on experience with dbt, treating transformation as software engineering with Git workflows, code review, and automated tests.
- Strong understanding of AI-assisted development workflows with proven hands-on experience using tools like Cursor, Claude, GitHub Copilot, or ChatGPT.
- Experience with spec-driven development: turning requirements into clear specs, plans, and acceptance criteria, then implementing them.
