Senior Data Engineer (Enterprise, Slack)

Role Overview

Join Slack as a Senior Data Engineer on the Enterprise team. You will design, build, and scale batch and real-time data pipelines and translate complex business requirements into reusable, scalable data models. This role also contributes to GovSlack, aiming to establish feature parity for U.S. government agencies and other highly regulated organizations.

Key Missions

• Design, build, and scale batch and real-time data pipelines
• Support initiatives serving enterprise decision-makers
• Translate complex business requirements into evolvable data models (scalable and reusable)
• Champion data strategy across multiple teams

Responsibilities

• Build and maintain data pipelines in OLAP/data warehouse environments
• Optimize schemas and tune SQL for performance and scale
• Contribute to data governance frameworks and cross-team collaboration

Requirements

• 5+ years in data architecture, data modeling, master data management, or metadata management
• Strong Python and SQL proficiency
• Hands-on relational modeling, including columnar, star schema, snowflake, and dimensional modeling
• Experience with batch + real-time pipeline engineering
• Experience with Airflow or a comparable workflow orchestration tool
• Proven track record scaling ETL pipelines and optimizing schemas
• Familiarity with data governance, SDLC, and Agile
• U.S. citizen or lawful permanent resident, willing to undergo background checks for GovSlack authorization

Nice-to-haves / Additional Skills

• Spark SQL
• AWS (S3, EMR)
• Apache Pinot or Hadoop/Big Data ecosystems
• Flink (or other real-time stream processing frameworks)
• Cloud platform familiarity (AWS, GCP, or Azure)
• Scala proficiency
• Experience with NoSQL data stores