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Senior Data Engineer, AI & Agents

Appnovation Technologies
Toronto, CAN
Senior · 5+ years experience
Discovered 1 months ago
airflowawsdatabricksdbtgiticeberg

Full Job Posting

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).
  • Experience implementing data quality, observability, and lineage, and applying governance controls such as masking and row- and column-level security.
  • Excellent stakeholder-facing skills, with a track record of translating business requirements into delivered data assets.

Preferred Skills

Familiarity with MCP-based data exposure and with embeddings or vector search for retrieval-augmented use cases.

Experience with AWS and S3, in anticipation of onboarding native cloud data sources.

Experience with regulated life-sciences data domains (clinical, commercial, or real-world data).

Technical Experience

Data platforms: Databricks, Snowflake (Cortex, Genie); AWS and S3.

Pipelines and modelling: SQL, PySpark, dbt, Airflow / Databricks Workflows.

Governance and catalogue: Unity Catalogue, Horizon, Collibra.

AI and agents: MCP; vector databases and embeddings.

Foundations: Python; YAML data contracts; Apache Iceberg; Git and CI/CD.

Who you are

Agent-Oriented Builder: You enjoy turning governed datasets into reliable, domain-grounded agents that business users can query with confidence.

Quality-Focused: You are rigorous about data accuracy, lineage, and observability, ensuring high standards through validation before data reaches agents or the business.

Collaborative Partner: You thrive working directly with stakeholders and subject-matter experts through iterative build, test, and validation cycles.

Governance-Minded: You understand the critical nature of data security in regulated domains and proactively apply masking and row- and column-level controls.

Forward-Thinking: You are interested in the “big picture” of lakehouse architecture and open formats, eager to advance agent-based access patterns and best practices.

What Appnovation Offers

Challenging and rewarding work with real impact

Direct Access to Cutting-Edge AI Platforms

Diverse and Inclusive Culture

Growth opportunities for personal and professional development

A collaborative and innovative work environment where your ideas are valued

Exposure to exciting projects and high-profile clients

Supportive work environment with access to company leaders

Hybrid working model

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