Senior Staff Data Engineer, AI Data Lake & ML Platform

Salesforce, Inc.; United States; Remote; USD 180,000 - 300,000; Full time

Job summary

Salesforce, a leader in AI-powered CRM, seeks a Senior Staff Data Engineer to own our foundational data lake infrastructure, ensuring reliable pipelines for ML training data. You will optimize Iceberg tables, design complex Airflow DAGs, and uphold data contracts across engineering teams.

Join the Machine Learning & Innovation team within Digital Enterprise Technology to drive high-velocity data transformations, enforce schemas, and deliver data-as-a-product capabilities at scale.

Qualifications

• Minimum 15+ years in data engineering and distributed processing.
• Deep expertise with modern data lake architectures and Snowflake.
• Strong SQL optimization and Python or Scala programming.
• Experience integrating ML feature stores and data contracts.

Responsibilities

• Own data lake infrastructure and Iceberg table maintenance.
• Architect Snowflake-to-lake Airflow DAGs for large-scale transforms.
• Design robust data pipelines with strict schemas and time-partitioning.
• Integrate offline stores with ML feature platforms for training data.
• Troubleshoot data quality, pipeline failures, and performance bottlenecks.
• Establish data-as-a-product practices with SLAs and lineage tracking.

Skills

15+ years experience

Data engineering

Distributed data processing

SQL optimization

Python or Scala

Education

Bachelor's degree in CS/Engineering

Tools

Apache Iceberg

Delta Lake

Snowflake

Apache Spark

EMR

Apache Airflow

Zipline

Feast

Job description

Salesforce, a leader in AI-powered CRM, seeks a Senior Staff Data Engineer to own our foundational data lake infrastructure, ensuring reliable pipelines for ML training data. You will optimize Iceberg tables, design complex Airflow DAGs, and uphold data contracts across engineering teams.

Join the Machine Learning & Innovation team within Digital Enterprise Technology to drive high-velocity data transformations, enforce schemas, and deliver data-as-a-product capabilities at scale.