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Quandri

Senior Data Engineer

Vancouver, BC, Canada

Experience: At least 4 to 6 years of professional data engineering experience.
Posting language: English
Posted: Oct 1, 2026

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Original job description

Who we are

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.

For the first time ever, we have the technology to fundamentally change how insurance operates, and the stakes are human. Better insurance means families protected from harm, businesses able to take risks, and communities more resilient when the worst happens. For insurance practitioners, the ability to deliver this level of service finally becomes possible.

What we do

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. Yet operating an agency is harder than ever. 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.

Why join us?

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.

We are headquartered in beautiful Vancouver, BC, backed by leading US and Canadian investors, and the recognition has followed:

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.

What you’ll do:

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.

The right person for this role will have:

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; 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

Our guiding principles:

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.

Compensation and Benefits:

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)

Quandri is dedicated to fostering a diverse and inclusive workplace. 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.

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.

\n\n

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More about this job

Responsibilities

You will own the end-to-end Databricks data lake, including dbt models, streaming ingestion, and AI data infrastructure. You will also collaborate with software, AI, and ML engineers to align on requirements and mentor team members in data best practices.

Requirements

The role requires 4 to 6 years of professional data engineering experience with proficiency in Python and SQL. Candidates must have hands-on experience with cloud platforms, data modeling, and building or supporting AI products.

Skills

Data engineering
Python
SQL
Databricks
Dbt
Data modeling
Cloud platforms
AWS
Azure
GCP
Data governance
AI infrastructure
Vector databases
Change data capture
Data pipelines
Data visualization

Benefits

Employee stock options
Comprehensive health benefits
Lifestyle spending account
Paid vacation
Parental leave top-ups

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
AI
Databricks
Dbt
Python
SQL
AWS
Azure
GCP
HubSpot
Postgres
DynamoDB
Vector Databases
LLM
Data Governance
Medallion Architecture
Star Schema
Snowflake Schema
Apache Airflow
Dagster
Tableau
Power BI
Insurtech
Machine Learning
Data Pipelines
Cloud Databases
CDC
Infrastructure
Data Analytics
API

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