Staff Software Engineer (Data Infrastructure)

• 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

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