Senior Data Engineer, AI & Agents

About Us

Appnovation is a global, full-service digital partner that combines Strategy, Experience & Design, Engineering and Managed Services. We build digital solutions that deliver real impact today and serve as foundations for future growth. Bold ambition. Practical action. Endless possibilities.

Appnova tion is a global, full-service digital partner that combines Strategy, Experience & Design, Engineering and Managed Services. We build digital solutions that deliver real impact today and serve as foundations for future growth. Bold ambition. Practical action. Endless possibilities.

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.

• 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.

• 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.

• 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).

• 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.

• 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…