Senior Data Engineer

A Note on Location

We are excited to meet with qualified candidates and are grateful for everyone’s interest. Please note that this is a remote position requiring applicants to be within commuting distance of Toronto for in person meetings 1-2 times a quarter
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Data sits at the center of how Blue J operates and scales. As our first dedicated Data Engineer, you will own the analytics data platform — not just the warehouse and models, but the standards, patterns, and guardrails that allow the rest of the organization to produce and consume data with confidence. Your goal is to build the foundation that lets teams own their own data products while maintaining quality, consistency, and trust across the business.

This role combines technical ownership, governance design, and stakeholder partnership. You'll balance hands‑on building with enabling others — centralizing the standards so ownership can be distributed.

• Own and maintain the Snowflake data warehouse, ensuring reliability, performance, and scalability
• Manage core Fivetran data ingestion pipelines, monitoring freshness, schema changes, and failures
• Build and maintain dbt models, including staging, intermediate, and gold-level data marts
• Define and enforce standards for data ingestion, modeling, testing, documentation, and consumption — so teams across the org can own their data products with confidence
• Set expectations for data producers (e.g., teams building features that generate data) around schema management, freshness, quality, and lifecycle ownership
• Optimize table design, naming conventions, semantic layers, and documentation to reduce dependency on ad‑hoc requests and eliminate duplicate logic

• Design and maintain analytics‑ready data marts that serve core business use cases (GTM, Finance, Product, Engineering, Leadership)
• Establish clear definitions for primary company KPIs, with shared ownership and alignment across stakeholder teams
• Partner with domain experts to ensure metrics are accurate, trusted, and consistently interpreted
• Implement testing, freshness checks, and validation to protect data quality

• Act as a central intake point for analytics and data requests across departments
• Coach and support teams that are building or maintaining their own data products within the platform
• Balance short‑term requests with longer‑term platform, governance and modeling investments
• Communicate tradeoffs clearly and set realistic expectations on delivery timelines

• Monitor Snowflake usage and costs, identifying inefficient queries, models, or usage patterns
• Optimize warehouse design, clustering, materialization strategies, and compute usage
• Partner with stakeholders to encourage efficient consumption patterns without slowing teams down
• Proactively flag cost risks and recommend mitigation strategies

• A minimum of 6 years of experience in Data Engineering, Analytics Engineering, or a closely related role
• A minimum of 2 years of hands‑on experience owning a Snowflake data warehouse in a production environment
• Strong experience with dbt, including model design, testing, and documentation
• Experience managing data ingestion tools such as Fivetran (or similar)
• A solid understanding of data engineering best practices, including dimensional modeling and metric governance
• Comfort working cross‑functionally with Marketing, Sales, Customer Success, Finance, Product, and Operations
• Experience prioritizing competing stakeholder requests in a fast‑moving environment
• Familiarity with BI tools and how downstream users interact with data
• A pragmatic mindset: you care about correctness, scalability, and cost—but also about enabling teams to move fast
• Experience working in B2B SaaS and/or a scaling, high‑growth environment

• A rare opportunity to own and shape the analytics foundation at a high‑growth, AI‑powered company.
• High visibility and impact—your work directly influences how leaders and teams make decisions.
• We’re well‑funded and offer competitive base…