Sr. Data Engineer, Enterprise - Slack

Slack•McLean, VA

About The Position

As a Data Engineer on the Enterprise team at Slack, you will partner cross-functionally with business stakeholders, analytics teams, and backend engineers to design, build, and scale both batch and real-time data pipelines. You will 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 will 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.

Requirements

5+ years of experience in data architecture, data modeling, master data management, or metadata management
Hands-on expertise with relational modeling approaches — including columnar, star schema, snowflake, and dimensional modeling
Proven track record optimizing schemas, tuning SQL, and scaling ETL pipelines in OLAP and data warehouse environments
Experience with Airflow or a comparable workflow orchestration platform for data pipeline management
Strong proficiency in Python and SQL
Familiarity with data governance frameworks, SDLC, and Agile methodologies
Excellent written and verbal communication skills with the ability to partner effectively across technical and business teams
U.S. citizen or lawful permanent resident, willing to undergo a background check for GovSlack authorization

Nice To Haves

Hands-on experience with Spark SQL, AWS (S3, EMR), Apache Pinot, or Hadoop/Big Data ecosystems
Experience with Flink or other real-time stream processing frameworks
Proficiency in Scala
Familiarity with cloud platforms (AWS, GCP, or Azure)
Experience with NoSQL data stores

Responsibilities

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