Lead Data Engineer (Artificial Intelligence)

Role overview

Join Salesforce as a Lead Data Engineer in the Data & Analytics organization. You’ll design and scale the data infrastructure that powers AI agents, acting as the primary architect for retrieval systems and driving operational excellence.

Responsibilities

• Lead the design and architecture of search and retrieval systems, ensuring robust search indices and high-precision retrieval across the Salesforce data ecosystem.
• Collaborate cross-functionally to define and execute the technical vision for agentic data delivery and shape the long-term roadmap.
• Mentor and elevate the team by fostering technical excellence and continuous growth; serve as a technical pillar for a specialized group of data and AI engineers.

Requirements

• 8+ years of experience in data engineering or a closely related role.
• Proficiency in Python, SQL, and distributed processing frameworks (e.g., Spark).
• Strong foundation in data modeling, database concepts, and data warehousing (SQL and NoSQL).
• Experience with cloud data platforms: AWS, Azure, or Google Cloud.
• Experience with the Salesforce ecosystem, including Data Cloud.
• Proven ability to communicate technical concepts clearly and collaborate across cross-functional teams.
• Hands-on experience with ETL/ELT tools such as Airflow, dbt, or Informatica.
• Experience building semantic search indices, embedding pipelines, or RAG (retrieval-augmented generation) systems.
• Familiarity with vector databases and AI/ML infrastructure.
• Experience partnering with Data Science/Decision Science teams on causal or attribution modeling.
• Track record of mentoring engineers and driving technical standards at team or org level.

Nice-to-haves

• A related technical degree (required per posting).