Product Data Engineer

Slack is looking for experienced Product Data Engineers to partner with our Analytics team and help drive the understanding, growth, and success of the product. The right candidates will have deep technical skills, be comfortable working in a nascent data infrastructure, and excited about building a strong data foundation for the analytics team. They will be scrappy, independent, and excited about having a big impact at Slack.

Our data engineers work closely with Product Analysts, Product Managers, and Engineering Teams to implement logging, own core datasets and build data tools to help enable Slack’s product teams. We're looking for Data Engineers to fill roles within all four pillars of Slack’s product teams: Core Product, Enterprise, Platform and Growth.


  • Manage and add new core datasets that power analytics and visualizations to support product team decision making.
  • Implement and help enforce a cohesive strategy for both logging and ETL pipelines.
  • Build data visualizations and reporting on top of core datasets
  • Work closely with analysts and product teams to understand current and future data needs.
  • Serve as the data expert and own data quality for areas of product ownership.
  • Define and manage SLA for all data sets in allocated areas of ownership.
  • Work with data infrastructure to triage infra issues and drive to resolution.
  • Find potential opportunities for building new tools to scale and provide self-service solutions


  • BS/BA in Technical Field, Computer Science or Mathematics.
  • 3+ years experience in the data warehouse space.
  • 3+ years experience in custom ETL design, implementation and maintenance.
  • 3+ years experience working with either a Map Reduce or an MPP system.
  • 3+ years experience with object-oriented programming languages (e.g. Python or Java preferred)
  • 3+ years experience with schema design and data modeling.
  • 3+ years experience in writing SQL statements.
  • 3+ years experience creating data visualization and reporting
  • Ability to analyze data infrastructure to identify opportunities for efficiency and improvements.
  • Excellent communication skills including the ability to proactively identify data issues and drive to resolution.

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