Description:
We’re a tight-knit team of five.
What will you do?
- Design and own our data architecture – Lead the development of scalable, secure data infrastructure to support onboarding and automation for mid-sized accounting firms.
- Build robust pipelines – Create, monitor, and optimize ETL/ELT workflows that integrate structured and unstructured data from accounting platforms like QuickBooks, Xero, Karbon, and Keeper.
- Enable AI workflows – Help structure and pipeline the right data to support LLM- and embedding-powered automation features in bookkeeping and operational workflows.
- Move fast & iterate – You thrive in startup environments and are comfortable building scrappy solutions that evolve with product needs.
- Think like a founder – You identify and solve problems independently, and work cross-functionally to drive outcomes that help the business scale.
What are we looking for?
- A mid to senior level Data Engineer with 3+ years of experience designing and building scalable data systems
- Must have worked in a fast-paced early-stage startup (Seed to Series A) or been a founding technical hire
- Strong experience building ETL/ELT pipelines across modern data stacks (e.g. Fivetran, dbt, Airflow, etc.)
- Experience ingesting, transforming, and analyzing messy data from third-party platforms and APIs (bonus: experience with accounting or finance data)
- Comfortable architecting warehouse/lakehouse solutions using tools like Snowflake, BigQuery, or Redshift
- Bonus: Experience structuring data to support LLM workflows (embeddings, chunking strategies, retrieval pipelines, etc.)
- Comfortable working in a remote work environment (option to work in the office always available at 111 Peter Street in downtown Toronto)
- Must have Canada or US Full-time Work Permit