Senior Data Engineer, AI & Agents
A senior data engineer who prepares enterprise domain data for AI agents: building domain-grounded data agents over governed datasets on Databricks and Snowflake, running lakehouse migrations to open formats like Apache Iceberg, and curating catalogue metadata for data contracts. Day to day is hands-on SQL/PySpark pipeline work plus close collaboration with business stakeholders in a hybrid Toront
- Compensation
- Not disclosed
- Location
- Toronto
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Contract
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field
- 5+ years of professional data engineering experience with modern data warehousing and lakehouse platforms (Databricks and Snowflake preferred)
- Hands-on fluency across both Databricks and Snowflake
- Experience building data agents or query interfaces over governed datasets (e.g., Snowflake Cortex or Genie)
- Advanced SQL plus Spark/PySpark and pipeline orchestration experience (dbt, Apache Airflow, or Databricks Workflows)
- Experience implementing data quality, observability, and lineage, and governance controls such as masking and row/column-level security
- Excellent stakeholder-facing skills, translating business requirements into delivered data assets
Nice to have
- Familiarity with MCP-based data exposure and embeddings/vector search for retrieval-augmented use cases
- Experience with AWS and S3
- Experience with regulated life-sciences data domains (clinical, commercial, or real-world data)
Full description
About us
Appnovation is the AI Product Company. Headquartered in Vancouver, Canada, with teams around the world, Appnovation builds AI products, delivers enterprise AI and digital solutions, and co-invests with clients to bring new AI products to market.
Open source has been the foundation of Appnovation's work since 2007, and it remains the foundation underneath every AI product the company builds today. Appnovation teams work with organizations in highly regulated industries, including global leaders such as Pfizer, Google and AstraZeneca, to help them adopt AI they can govern and own.
As a Senior Data Engineer, AI & Agents, you will prepare enterprise domain data for consumption by AI agents, partnering directly with business stakeholders and subject-matter experts. The role centers on building and registering domain-grounded data agents over governed datasets, performing lakehouse migrations, and onboarding new data domains — including commercial, finance, research and development, and real-world data — onto the enterprise data platform. You will operate across Databricks and Snowflake, converting source tables to open formats and generating the catalogue metadata that powers downstream automation and data-contract workflows, all while ensuring high data quality, governed access, and reliable agent-based access to trusted data. The ideal candidate brings deep, hands-on data engineering expertise, strong governance instincts, and excellent stakeholder-facing skills.
Key Responsibilities
- Build and register domain data agents at scale over governed tables across Databricks and Snowflake.
- Perform lakehouse migrations, including converting source tables to open formats (e.g., Apache Iceberg) to enable agent-based access.
- Generate and curate catalogue metadata that feeds downstream automation and data-contract workflows.
- Partner with business stakeholders and subject-matter experts through iterative build, test, and validation cycles.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related field.
- 5+ years of professional experience in data engineering, with significant hands-on experience across modern data warehousing and lakehouse platforms (Databricks and Snowflake preferred).
- Strong data engineering background with genuine, hands-on fluency across both Databricks and Snowflake.
- Demonstrated experience building data agents or query interfaces over governed datasets (e.g., Snowflake Cortex or Genie).
- Advanced SQL together with Spark / PySpark, and experience with pipeline orchestration (dbt, Apache Airflow, or Databricks Workflows).