Salesforce, Inc..
Senior/Lead/Principal Data Engineer
Office hybrid in San Francisco, Dallas or Seattle
About the Role
We’re building the
product data platform
that will power Salesforce’s next era of
agentic intelligence
— delivering smarter, adaptive, and self-optimizing product experiences.
As a
Full-Stack Data Engineer , you’ll design and build scalable systems that process hundreds of thousands of context-rich product signals. These signals fuel analytics, customer-facing products, ML models, and autonomous agents. You’ll work on:
Near real-time and batch telemetry pipelines for trusted signal capture
Semantic layers and data products for reusable insights
Programmatic discovery via metadata, MCP, and knowledge graphs
This isn’t a typical data engineering role. We’re looking for
creative, systems-minded engineers
working outside of the “data engineer” box, fluent in both
data and AI , and excited to navigate ambiguity, cross boundaries, and drive real impact.
What You’ll Do
Build and scale fault tolerant
batch and streaming data pipelines
using Spark, Trino, Flink, Kafka, DBT
Design
programmatic consumption layers
to make product signals easy to define, discover, and reuse
Apply
software engineering best practices
to data systems: testing, CI/CD, observability
Evolve systems to support not just human analysis, but
autonomous agent reasoning
Contribute to a
trusted data foundation
powering decisions, AI agents, and adaptive products
Collaborate
across orgs
with telemetry engineers, product leaders, data scientists, and AI builders
What We’re Looking For
5+ years of experience in
data engineering , with strong
software engineering fundamentals
Expertise with
big data frameworks : Spark, Trino/Presto, DBT
Experience with
streaming systems
like
Flink
and
Kafka , incl. distribution strategy (topics & partitions)
Solid understanding of
semantic layers ,
data modeling , and
metrics systems
Experience with
cloud infrastructure , particularly
AWS (e.g., S3, EMR, ECS, IAM), Containerization
Bonus: fluency in
AI data engineering
patterns and tools like MCP
Bonus: experience with
knowledge graphs
and
modern metadata systems
Bonus: experience with
Snowflake
Strong
communicator
and
collaborator
— comfortable working across teams and domains
Curious, pragmatic, and
impact-driven mindset
Why Join Us Help shape how Salesforce leads the digital labor revolution. You’ll be at the heart of transforming raw product signals into intelligent decisions — for everyone from engineers to sales reps to AI agents. If you’re excited to design resilient, trusted, and intelligent systems at scale, we’d love to hear from you.
#J-18808-Ljbffr
product data platform
that will power Salesforce’s next era of
agentic intelligence
— delivering smarter, adaptive, and self-optimizing product experiences.
As a
Full-Stack Data Engineer , you’ll design and build scalable systems that process hundreds of thousands of context-rich product signals. These signals fuel analytics, customer-facing products, ML models, and autonomous agents. You’ll work on:
Near real-time and batch telemetry pipelines for trusted signal capture
Semantic layers and data products for reusable insights
Programmatic discovery via metadata, MCP, and knowledge graphs
This isn’t a typical data engineering role. We’re looking for
creative, systems-minded engineers
working outside of the “data engineer” box, fluent in both
data and AI , and excited to navigate ambiguity, cross boundaries, and drive real impact.
What You’ll Do
Build and scale fault tolerant
batch and streaming data pipelines
using Spark, Trino, Flink, Kafka, DBT
Design
programmatic consumption layers
to make product signals easy to define, discover, and reuse
Apply
software engineering best practices
to data systems: testing, CI/CD, observability
Evolve systems to support not just human analysis, but
autonomous agent reasoning
Contribute to a
trusted data foundation
powering decisions, AI agents, and adaptive products
Collaborate
across orgs
with telemetry engineers, product leaders, data scientists, and AI builders
What We’re Looking For
5+ years of experience in
data engineering , with strong
software engineering fundamentals
Expertise with
big data frameworks : Spark, Trino/Presto, DBT
Experience with
streaming systems
like
Flink
and
Kafka , incl. distribution strategy (topics & partitions)
Solid understanding of
semantic layers ,
data modeling , and
metrics systems
Experience with
cloud infrastructure , particularly
AWS (e.g., S3, EMR, ECS, IAM), Containerization
Bonus: fluency in
AI data engineering
patterns and tools like MCP
Bonus: experience with
knowledge graphs
and
modern metadata systems
Bonus: experience with
Snowflake
Strong
communicator
and
collaborator
— comfortable working across teams and domains
Curious, pragmatic, and
impact-driven mindset
Why Join Us Help shape how Salesforce leads the digital labor revolution. You’ll be at the heart of transforming raw product signals into intelligent decisions — for everyone from engineers to sales reps to AI agents. If you’re excited to design resilient, trusted, and intelligent systems at scale, we’d love to hear from you.
#J-18808-Ljbffr