Q

Quandri

Automates repetitive tasks for insurance brokerages

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeVancouver, BC, Canada

About the Job

Requirements

  • At least 4 to 6 years of professional data engineering experience.
  • Demonstrated experience 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 and SQL; Python is preferred.
  • Experience designing multi-tenant data systems with hard isolation requirements and handling personally identifiable information or other regulated data.
  • Proficiency in data modeling, medallion architecture, star schema, or Snowflake schema.
  • Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
  • Experience with dbt, Databricks Workflows, Apache Airflow, Prefect, 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, Tableau, or Power BI equivalents.
  • Experience building or supporting AI products.
  • Proficiency in data governance.

Responsibilities

  • Own the Databricks data lake end to end, including dbt models, medallion layers, incremental and backfill strategy, partitioning, freshness, and quality monitoring.
  • Establish change-data-capture and streaming ingestion from HubSpot, Langfuse, Postgres, and DynamoDB into the data lake, including idempotency and deduplication.
  • Own data services, schema and migration strategy, versioned APIs, provenance and audit trails, and the associated tests and observability.
  • Build AI data infrastructure, including embedding pipelines, vector stores, retrieval knowledge bases, feature stores, and large language model 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 and machine learning engineers, data scientists, product, and business units to align on requirements and communicate technical concepts clearly to non-technical stakeholders.
  • Guide and mentor engineers in data best practices.

Desired Qualifications

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

About the Company

Quandri

Automates repetitive tasks for insurance brokerages

Quandri builds customized digital workers, or software bots, that automate repetitive and time-consuming tasks for insurance brokerages. These bots handle routine operations such as quoting and suspending policies, enabling agencies to save time and money and free human staff for more valuable tasks. The product works by developing, deploying, and maintaining automation solutions tailored to an insurance workflow; clients pay for the initial setup plus ongoing support, creating a predictable revenue model. Quandri differentiates itself by offering tailored, end-to-end automation for the insurance brokerages sector, providing cost savings that are typically smaller than hiring more staff but with ongoing service to ensure smooth operation. The company's goal is to increase efficiency and reduce operating costs for insurance agencies by handleing repetitive tasks automatically, helping them grow and improve customer satisfaction.

Company size
51-200
Company stage
Series A
Total funding
$22M
Headquarters
Vancouver, Canada
Founded
2020

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