Staff Software Engineer, Data Infrastructure

Slack is looking for a Staff Software Engineer to join the Data Infrastructure team within the broader Data Engineering organization. The mission of our team is to build secure, reliable, performant, scalable, and cost-efficient infrastructure with an AI-forward approach that powers Slack’s data ecosystem.

We design and operate the core data platforms that enable data engineers, analysts, and machine learning practitioners to deliver trusted insights and data products across Slack.

Our systems power critical workflows — from batch and streaming ingestion to real-time analytics and orchestration. We’re looking for strong technical leaders who can combine hands-on expertise with strategic impact and mentorship-driven leadership to scale, and evolve the backbone of Slack’s data infrastructure.

You’ll play a key role in the design, development, and operation of services that underpin data ingestion, transformation, storage, compute and orchestration at a massive scale. As a Staff Engineer, you’ll be a Directly Responsible Individual (DRI) for multiple core data services, accountable for uptime, reliability, and performance, and a subject matter expert (SME) across multiple systems.

Here are a few examples of what we work on:

• Scaling our compute and orchestration layer with an AI-forward and data driven approach.
• Enabling more realtime OLAP capabilities for internal and external customers
• Creating and scaling agents, AI skills, and automation to enable engineers and users on their workflow and data needs
• What you will be doing
• Design, build, and operate reliable and scalable data infrastructure powering Slack’s analytics, ML, and data-driven decision-making.
• Serve as DRI for multiple core data services specifically on our analytics infrastructure (e.g. Pinot, and Trino), ensuring uptime, reliability, and our compute and orchestration services (e.g., Airflow, Spark on Kubernetes, EMR, Hive Metastore).
• Drive improvements in security, cost efficiency, and developer experience across our data infrastructure.
• Build automation and self-service tools that empower our team and other data teams to easily adopt and manage data workflows.
• Collaborate closely with data engineering, platform, and security teams to design scalable, well-governed solutions.
• Build and enhance our observability, monitoring, and alerting on our services via Grafana and related tooling.
• Partner with other staff and senior engineers to define best practices, technical standards, and support models for Slack’s data ecosystem.
• Mentor and coach other engineers, modeling ownership, collaboration, and operational excellence.

What you should have

• 10+ years of software, platform, or infrastructure engineering experience, including time spent supporting data-intensive systems or data platforms.
• First-class communication skills and the ability to collaborate across cross-functional teams.
• Proven experience in building, deploying, and operating distributed infrastructure at scale.
• Strong technical background with big data and infrastructure technologies — such as EMR, Airflow, Pinot, Trino, Hive Metastore, Kubernetes, or equivalent systems.
• Proficiency in Python, Golang, Bash, and SQL.
• Proficiency with CI/CD (GitHub Actions), Vault, Terraform, Chef, and Grafana.
• Deep understanding of infrastructure reliability, observability, and cost efficiency principles.
• Hands-on experience supporting data pipelines or data engineering workflows is a strong plus.
• A strong sense of ownership and a drive to deliver high-impact, autonomous results.
• Hands-on experience building, managing, and integrating agentic workflows, custom AI skills, automated software factory pipelines, MCP
• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.

What we value

Slack has a positive, diverse, and supportive culture—we look for people who are curious, inventive, and collaborative. We seek engineers who care deeply about craftsmanship, reliability, and empowering others. In our work together, we strive to be smart, humble, hardworking, and—above all—collaborative.