Senior Data Engineer (Enterprise, Slack)

Salesforce; San Francisco (CA); On-site; USD 140,000 - 230,000; Full time

Benefits offered by this job

Medical Care

Life Insurance

Retirement Savings

Employee Assistance Programs

13 paid days off per year

Job summary

Salesforce is seeking a Data Engineer on the Enterprise team to design, build, and scale batch and real-time data pipelines. You will partner across business, analytics, and engineering teams to deliver high-quality data foundations and support GovSlack initiatives for government agencies.

You will translate complex requirements into scalable data models, ensure data quality under SLAs, and drive data strategy across multiple teams to enable trusted metrics for decision-makers.

Qualifications

• Hands-on expertise with relational modeling approaches and data architectures.
• Experience designing scalable data pipelines for batch and real-time processing.
• Strong Python and SQL programming skills.
• Experience with Airflow or similar workflow orchestration tools.
• Familiarity with cloud platforms (AWS, GCP, or Azure).
• Experience with Flink or real-time stream processing frameworks.

Responsibilities

• Design, build, and scale batch and real-time data pipelines.
• Partner with stakeholders to translate requirements into scalable data models.
• Develop trusted datasets aligned with business strategy.
• Champion data strategy and promote best practices across teams.
• Expand access to core metrics through robust data foundations.

Skills

Python

SQL

Airflow

Spark SQL

AWS

Data Modeling

Scala

Tools

Hadoop/Big Data ecosystems

Pinot

Job description

• As a Data Engineer on the Enterprise team, you’ll partner cross-functionally with business stakeholders, analytics teams, and backend engineers to design, build, and scale both batch and real-time data pipelines
• You’ll contribute directly to initiatives that support key decision-makers within our enterprise customer base — helping them understand adoption, engagement, and the health of their Slack deployments
• You’ll also be a core contributor to GovSlack, our cross-team initiative to establish feature parity for U.S. government agencies and highly regulated organizations
• This is high-visibility, high-impact work that matters beyond the product — it supports national infrastructure
• We’re looking for passionate, detail-oriented engineers who are excited about building a rock-solid data foundation and making a real impact at one of the world’s most widely used collaboration platforms
• Translate complex business requirements into scalable, reusable data models that are easy to understand and adopted across subject areas
• Design, implement, and maintain data pipelines that deliver high-quality data under defined SLAs
• Partner with product, analytics, and engineering teams to build trusted, well-documented foundational datasets aligned with business strategy
• Champion data strategy across multiple teams and use cases, driving consistency and reliability at scale
• Expand access to core company metrics through strong technical and process foundations
• Identify, document, and promote data engineering best practices across Slack

Benefits

• Medical Care
• Life Insurance
• Retirement Savings
• Employee Assistance Programs
• With 9 standard holidays and four floating holidays, you get a total 13 paid days off each year

Hands-on expertise with relational modeling approaches — including columnar, star schema, snowflake, and dimensional modelingU.S. citizen or lawful permanent resident, willing to undergo a background check for GovSlack authorizationProven track record optimizing schemas, tuning SQL, and scaling ETL pipelines in OLAP and data warehouse environmentsFamiliarity with data governance frameworks, SDLC, and Agile methodologiesStrong proficiency in Python and SQLExperience with Airflow or a comparable workflow orchestration platform for data pipeline management5+ years of experience in data architecture, data modeling, master data management, or metadata managementExcellent written and verbal communication skills with the ability to partner effectively across technical and business teamsExperience with Flink or other real-time stream processing frameworksHands-on experience with Spark SQL, AWS (S3, EMR), Apache Pinot, or Hadoop/Big Data ecosystemsProficiency in ScalaFamiliarity with cloud platforms (AWS, GCP, or Azure)Experience with NoSQL data stores