Posted by the employer · United States
Senior Data Engineer - AI & Agents
Appnovation Technologies · United States
Posted: 9/4/2026 · On the employer's job feed since 10/11/2026
The advert
Quoted in full from Appnovation Technologies's job posting. Gavroche does not edit it.
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.
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).
- 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
Accommodations are available upon request throughout the recruitment process.
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200 open data engineer roles found; at most three per employer shown. Source: Direct employer job feeds (ATS) and career sites crawled by gavroche-direct.
How data engineer roles in United States are worked
9% fully remote · 0% hybrid · 91% on-site
From 43 adverts whose ATS states a work mode. Source: Direct employer job feeds (ATS) and career sites crawled by gavroche-direct; the employers' own work-mode flags (adverts without one count as on-site).
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41 open. Source: Direct employer job feeds (ATS) and career sites crawled by gavroche-direct.