Senior Data Engineer (Enterprise, Slack)

• 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 modeling

• U.S. citizen or lawful permanent resident, willing to undergo a background check for GovSlack authorization

• Proven track record optimizing schemas, tuning SQL, and scaling ETL pipelines in OLAP and data warehouse environments

• Familiarity with data governance frameworks, SDLC, and Agile methodologies

• Strong proficiency in Python and SQL

• Experience with Airflow or a comparable workflow orchestration platform for data pipeline management

• 5+ years of experience in data architecture, data modeling, master data management, or metadata management

• Excellent written and verbal communication skills with the ability to partner effectively across technical and business teams

• Experience with Flink or other real-time stream processing frameworks

• Hands-on experience with Spark SQL, AWS (S3, EMR), Apache Pinot, or Hadoop/Big Data ecosystems

• Proficiency in Scala

• Familiarity with cloud platforms (AWS, GCP, or Azure)

• Experience with NoSQL data stores