Staff Data Engineer (AI)

Location: California - San Francisco, United States; other listed location: New York, New York. Workplace type: Office Tech-Flexible.

Base salary: $197,300–$313,700 annually. In select cities within the San Francisco and New York City metropolitan areas: $237,700–$344,700 annually.

Company

hirify.global's Data Engineering organization operates within Salesforce's Data & Insights organization and builds collaboration, analytics, and AI-powered workplace products.

What you will do

• Set the architecture and roadmap for the metrics platform, covering ingestion, canonical datasets, semantic layers, and serving.
• Design and scale data models and pipelines that transform billions of records into trusted datasets with measurable quality, predictable SLAs, and freshness signals.
• Evolve semantic-layer capabilities and build APIs and tools that help people and AI agents navigate metric definitions, lineage, ownership, and accurate queries.
• Lead metric certification, governance, and design reviews while mentoring senior engineers.
• Serve as the technical lead for Agentic Analytics on the metrics side and drive alignment across Engineering, Product, Data Science, and Analytics.

Requirements

• 10+ years of software or data engineering experience, including 6+ years of hands-on experience with data architecture, data modeling, and metadata management.
• Experience leading complex, multi-team technical initiatives as an individual contributor and driving alignment without formal authority.
• Deep SQL expertise and strong Python skills, plus working proficiency in Go, Java, or Scala.
• Experience architecting scalable, cost-efficient data models and pipelines.
• Hands-on experience with Spark, Trino, Airflow, Iceberg, Snowflake, and dimensional and star/snowflake modeling.
• Related technical degree required.

Nice to have

• Experience building infrastructure or tools for AI agents, including Model Context Protocol servers, tool-use APIs, or evaluation harnesses.
• Experience with semantic layers, metrics platforms, data catalogs, or lineage tools such as dbt, sqlmesh, DataHub, Cube, or LookML.
• Experience with experimentation platforms, including metrics, exposure logging, and guardrails for A/B testing.
• Ability to prototype early, balance speed with judgment, and measure impact by what surrounding teams ship.

Culture & Benefits

• Senior individual contributor role with organization-wide scope and multi-quarter impact.
• Collaboration with Product, Data Science, Analytics, and Engineering teams.
• Benefits include time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program.
• Salesforce supports reasonable accommodations during the application and recruiting process and maintains an equal opportunity and non-discrimination policy.
• AI tools may assist recruiters in assessing resumes and qualifications, while humans make candidate selection and hiring decisions.