Our mission at Quandri is to transform insurance into a trusted and delightful experience using AI. We are building the AI operating system for North America’s best insurance agencies and brokerages. Better insurance means families protected from harm, businesses able to take risks, and communities more resilient when the worst happens.

Quandri brings deeply specific, vertically-focused AI to the industry’s most critical stakeholders:insurance agencies and brokerages. Agents are the lifeblood of the industry, the place where most property and casualty insurance is sold and serviced. Peak product complexity, accelerating consolidation, a deepening talent crisis, and the AI revolution are all reshaping how agencies work.

Quandri sits at the cutting edge of this shift, rebuilding how agencies operate one workflow at a time. We pair a deep understanding of insurance processes, systems, and data with serious technical capability and proprietary models, so the transformation is tangible and operational rather than aspirational. We’re making insurance better for policyholders, while helping insurance brokerages deliver a better client service, grow faster, and harness AI so that they control the future of insurance distribution.

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 Bonus points if you have: Bachelor's or Master’s degree, preferably in Computer Science, Data Engineering, Computer Engineering, or related technical discipline;

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 commit ourselves to excellence in everything that we do, from delivering an amazing product to writing a outstanding email.

We follow through on commitments, own our results and think long-term. The law of increasing functional information states that systems evolve to become more complex over time. 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. Comprehensive health benefits, including $500 Lifestyle Spending Account Four weeks of paid vacation per year Parental leave top-ups: 6 months for birthing parents, 8 weeks for non-birthing parents (up to $100,000 annual salary) As an equal opportunity employer, Quandri adheres to Canadian labour laws and does not engage in discrimination based on race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or any other status protected under Canadian law. In our hiring process, that means using AI to handle the administrative and logistical work so our interviewers can show up more fully in every conversation with you.

AI tools support parts of our process, such as analyzing resumes and taking notes during interviews. But AI is never the decision maker. If you have questions about how your information is handled or how we use AI, don't hesitate to reach out.

📌 Senior Data Engineer (Python) - Remote (Vancouver)
🏢 Quandri
📍 Vancouver