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Salary: CAD 140,000 - 170,000 / annual
Quandri is building an AI operating system for North America's insurance agencies and brokerages, transforming how insurance operates through deeply specific, vertically-focused AI. The company is backed by leading US and Canadian investors and has been recognized as one of LinkedIn's Top Canadian Startups (2024 & 2025), included in Deloitte's Fast 50, CB Insights' Insurtech 50 and Fintech 100, and The Globe and Mail's Top Growing Companies in Canada.
As Senior Data Engineer, you will own the Databricks data lake end-to-end, including dbt models, medallion layers, incremental and backfill strategies, partitioning, freshness, and quality monitoring. You will stand up change-data-capture (CDC) and streaming ingestion from HubSpot, Langfuse, Postgres, and DynamoDB into the data lake, ensuring idempotency and deduplication. You'll own data services, schema and migration strategy, versioned APIs, provenance and audit trails, and the tests and observability behind them.
You will build AI data infrastructure including embedding pipelines, vector stores, retrieval knowledge bases, feature stores, and LLM observability. You'll develop and maintain cloud databases with the Infrastructure team, improve data retrieval, and optimize analytics dashboards. You'll maintain data management and security policies and work cross-functionally with software, AI/ML engineers, data scientists, product, and business units to align on requirements and communicate technical concepts to non-technical stakeholders. You'll also guide and mentor engineers in data best practices.
The company operates with guiding principles centered on customers, urgency, curiosity, execution excellence, ownership, simplicity, and an AI-first mindset. You'll join a fast-moving team with real ownership, direct access to leadership, and a genuine hand in shaping the company's next chapter.
REQUIREMENTS:
- At least 4 to 6 years of professional data engineering experience
- Demonstrated experience owning maintenance and implementation of databases, data pipelines, and backends with focus on efficient data management and integration
- Proficiency in Python (preferred) and SQL
- Experience designing multi-tenant data systems with hard isolation requirements and handling PII or regulated data
- Proficiency in data modeling, medallion architecture, star schema, or Snowflake schema
- Hands-on experience with cloud platforms (AWS, Azure, or GCP)
- Experience with dbt, Databricks Workflows, Apache Airflow, Prefect, Dagster or equivalent, change-data-capture tooling, or AWS Step Functions
- Proficiency in data visualization tools such as Databricks SQL dashboards, Tableau, or Power BI
- Experience building or supporting AI products
- Proficiency in data governance
BONUS:
- Bachelor's or Master's degree in Computer Science, Data Engineering, Computer Engineering, or related technical discipline (or equivalent experience)
- Experience communicating with senior leadership on requirements, software features, technical designs, and product strategy
- Experience building and hydrating vector databases like Pinecone or AWS Bedrock Knowledge Bases
