Software Engineering PMTS - Data Engineer

About the Team:
Digital Enterprise Technology (DET) at Salesforce builds the internal engines that power our business. The Machine Learning & Innovation (MLI) team is the applied science and infrastructure strike-force responsible for "Foundry," our unified ML/AI Platform. We operate as "Customer Zero," building the high-velocity, real-time streaming feature platforms and recommendation models that power internal products like the Events App and enterprise-wide personalization.
Role Overview:
As a Senior Staff Data Engineer, you will own the foundational data lake infrastructure that supplies all downstream machine learning models. You will build and maintain the massive, highly reliable data pipelines required to transform raw enterprise data into point-in-time correct training datasets and offline features, ensuring the lifeblood of our AI platform flows without interruption.
What You'll Do:
Manage and optimize the foundational data lake infrastructure, specifically focusing on Apache Iceberg table maintenance, compaction, and vacuuming.
Architect and maintain complex Snowflake-to-lake Airflow DAGs for massive-scale data transformations.
Design and implement robust data transformation pipelines, enforcing rigorous event schemas and time-partition column standards (e.g., ts/ds).
Integrate offline data stores with the Zipline feature platform to support automated historical backfills and point-in-time correct training data generation.
Troubleshoot and resolve complex data quality anomalies, pipeline failures, and performance bottlenecks in distributed data systems.
Establish Data-as-a-Product practices, defining clear data contracts, SLAs, and data lineage tracking mechanisms.
What You Bring:
15+ years of experience in data engineering, data architecture, and distributed data processing.
Deep expertise in modern data lake architectures (Apache Iceberg, Delta Lake) and data warehousing (Snowflake).
Advanced proficiency in distributed compute engines (Apache Spark, EMR) and workflow orchestration (Apache Airflow).
Expert-level SQL optimization skills and strong programming experience in Python or Scala.
Experience integrating offline data platforms with machine learning feature stores (Zipline, Feast).
A meticulous approach to data quality, schema enforcement, and pipeline reliability.

Employment type
Full time