below marketmost similar roles pay hereabove market
This role pays more than
82%
of similar roles. Most pay
$182,500–$245,882
— the blue band above.
At the midpoint, this role pays about
$256k
versus about
$214k
for comparable roles.
Based on 240 similar postings.
Employer
About Salesforce
Salesforce is the world''s leading customer relationship management (CRM) platform, offering cloud-based software for sales, service, marketing, analytics, and application development. Industry: Enterprise Software & Cloud Computing
Salesforce currently has
221 open roles
on FindRole.
Listed pay typically runs
$148,500–$260,100
across 125 roles with salary data.
Staff Software Engineer, Data Infrastructure joins the Data Infrastructure team within the broader Data Engineering organization at Slack. This role involves designing, building, and operating reliable, scalable data infrastructure to power analytics, machine learning, and data-driven decision-making. You will serve as a Directly Responsible Individual for core data services, specifically focusing on analytics infrastructure and compute orchestration. Key responsibilities include managing data ingestion, transformation, storage, and real-time OLAP capabilities while improving security, cost efficiency, and developer experience. You will utilize technologies including Python, Golang, Bash, SQL, Kubernetes, Spark, EMR, Airflow, Pinot, Trino, and Hive Metastore. Additionally, you will use GitHub Actions, Vault, Terraform, Chef, and Grafana to build automation, self-service tools, and observability for the data ecosystem.
What does a Software Engineer earn in California?
Median $214500 from 1193 postings across 76 companies.
Design, build, and operate scalable data infrastructure for analytics, machine learning, and data-driven decision-making.
Serve as the Directly Responsible Individual (DRI) for core analytics services like Pinot and Trino.
Manage compute and orchestration services including Airflow, Spark on Kubernetes, EMR, and Hive Metastore.
Drive improvements in security, cost efficiency, and developer experience across the data infrastructure.
Build automation and self-service tools to help other teams manage data workflows easily.
Enhance observability, monitoring, and alerting systems using Grafana and related tooling.
Define technical standards and best practices for the data ecosystem in partnership with other staff engineers.
Mentor and coach engineers on ownership, collaboration, and operational excellence.
What we're looking for
10+ years of software, platform, or infrastructure engineering experience, including time spent supporting data-intensive systems or data platforms.
Proven experience in building, deploying, and operating distributed infrastructure at scale.
Strong technical background with big data and infrastructure technologies such as EMR, Airflow, Pinot, Trino, Hive Metastore, Kubernetes, or equivalent systems.
Proficiency in Python, Golang, Bash, and SQL.
Proficiency with CI/CD (GitHub Actions), Vault, Terraform, Chef, and Grafana.
Hands-on experience supporting data pipelines or data engineering workflows (preferred).
Hands-on experience building, managing, and integrating agentic workflows, custom AI skills, automated software factory pipelines, and MCP (preferred).
Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
Must be a U.S. citizen (U.S. born or naturalized) who does not hold dual citizenship and can complete a U.S. federal government Minimum Background Investigation.
Data Infrastructure
Data Warehouse
Data Lakehouse
Apache Spark
Workflow Orchestration
Streaming Infrastructure
Python
Databricks
Airflow
AWS EMR
ETL
Machine Learning
System Design
Data Pipelines
Data Infrastructure
Data Warehouse
Data Lakehouse
Apache Spark
Workflow Orchestration
Streaming Infrastructure
Python
Databricks
Airflow
AWS EMR
ETL
System Design
Machine Learning
Data Pipelines