Senior Data Engineer, AI & Agents

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.

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.

• 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).

• 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

Thank you for your interest in a career with Appnovation Technologies! Please note that only those selected for an interview will be contacted.

Accommodations are available upon request throughout the recruitment process.

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.