• LinkedIn’s Top Canadian Startups in 2024 & 2025
• Deloitte’s Fast 50
• CB Insights’ Insurtech 50 and Fintech 100
• The Globe and Mail’s Top Growing Companies in Canada .

• Own the Databricks data lake end to end, dbt models, medallion layers, incremental and backfill strategy, partitioning, freshness, quality monitoring.
• Stand up CDC and streaming ingestion from HubSpot, Langfuse, Postgres, and DynamoDB into the data lake, with idempotency and dedup handled.
• Own data services, schema and migration strategy, versioned APIs, provenance and audit trails, the tests and observability behind them.
• Build AI data infrastructure, embedding pipelines, vector stores, retrieval knowledge bases, feature stores, LLM observability.
• Develop and maintain cloud databases with the Infrastructure team, improve data retrieval and optimize analytics dashboards.
• Maintain data management and security policies.
• Work with software/AI/ML engineers, data scientists, product, and business units to align on requirements, communicate technical concepts clearly to non-technical stakeholders.
• Guide and mentor engineers in data best practices.

• At least 4 to 6 years of professional data engineering experience.
• Demonstrated experience with owning the maintenance and implementation of databases, data pipelines and backends with a focus on efficient data management and integration of system components.
• Proficiency in Python (Preferred) and SQL.
• Experience designing multi-tenant data systems with hard isolation requirements, and handling PII or other regulated data.
• Proficiency in data modeling, medallion architecture, star schema, or Snowflake schema.
• Hands on experience with cloud platforms like AWS, Azure, or GCP.
• Experience with tools like, dbt, Databricks Workflows, Apache Airflow, Perfect, Dagster or equivalent, change-data-capture tooling, or AWS Step Functions for managing and automating data pipelines.
• Proficiency in data visualization tools such as Databricks SQL dashboards or Tableau / Power BI equivalent.
• Experience building or supporting AI products
• Proficiency in data governance

• Bachelor's or Master’s degree, preferably in Computer Science, Data Engineering, Computer Engineering, or related technical discipline; or equivalent experience.
• Experience in communicating with senior leadership to collect requirements, describe software product features, technical designs, and product strategy
• Experience with building and hydrating vector databases like Pinecone, or AWS Bedrock Knowledge Bases

• Customers at the core. We put the customer at the center of all we do. At a basic level, we believe business success comes down to talking to customers and building something they want. We don’t listen to customers and just take what they say blindly, but we think critically about it and build what they need. Customers are the core of everything we do, and our business exists to serve them. We prioritize their needs over all else within the company.
• Move with urgency. There are times when we need to move slowly and deliberately, but we default to acting fast and with urgency. We slow down when necessary, but this should be a deliberate choice. Businesses become more lethargic as they grow, this principle is designed to fight this fact.
• Be curious. We understand the world by being curious and asking why. We aren’t satisfied with surface level understanding, and seek a deeper understanding of why things are the way they are. Don’t take someone’s word for it or the answer “because that’s how we do it.” Understand why and dig deep.
• Excellence in execution. We know that what separates good from great is a high level of execution. We commit ourselves to excellence in everything that we do, from delivering an amazing product to writing a great email.
• Act like an owner. We’re all owners of the business and act like it. We follow through on commitments, own our results and think long-term.
• Fight for simplicity. The law of increasing functional information states that systems evolve to become more complex over time. At Quandri, we believe there is sophistication in simplicity; as such, we intentionally fight for streamlined solutions and are committed to the uncomplicated.
• AI-first. We believe AI is a fundamental shift in how work gets done, not just a tool we occasionally reach for. At Quandri, we lead with AI, in how we build our product, how we run our operations, and how we think about every process and workflow. This isn't about replacing people; it's about unlocking them to do higher-value work.

• The range for base pay is $140k - $170k which is dependent on level of experience
• Employee stock options, granted based off experience level upon hire and subject to a standard vesting schedule
• Employee stock options based on experience level
• Comprehensive health benefits, including $500 Lifestyle Spending Account
• Four weeks of paid vacation per year
• Work anywhere in the world for 60 calendar days of the year
• Parental leave top-ups: 6 months for birthing parents, 8 weeks for non-birthing parents (up to $100,000 annual salary)

Don’t let imposter syndrome stop you from applying. Great people sometimes don’t have the “right” experience. If you think that you’ll be amazing at this role then we encourage you to apply.