Member of Technical Staff, Data Pipelines and Data Platform

Pure Storage•Lehi, UT

1d•Onsite

About The Position

We’re in an unbelievably exciting area of tech and are fundamentally reshaping the data storage industry. Here, you lead with innovative thinking, grow along with us, and join the smartest team in the industry. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE As a Member of Technical Staff, you will bridge the gap between high-scale data engineering and platform resilience. You will champion SRE methodologies to transform raw system metrics into actionable health insights, directly influencing global infrastructure scalability. By automating complex pipelines and establishing SLOs, you’ll drive engineering efficiency and ensure our platform remains robust and performant for users worldwide through close collaboration with our SRE and Product teams.

Requirements

Systems & Data Programming: Proficiency in writing efficient, maintainable code (such as Python, Go, or Java) and a mastery of complex SQL for analyzing large-scale datasets and optimizing warehouse performance.
Modern Data Architecture: Practical experience with cloud-scale data environments (e.g., Snowflake, BigQuery, or ClickHouse) and implementing scalable data models within transformation frameworks like dbt.
Reliability Engineering Mindset: A strong understanding of SRE fundamentals, including automated testing, version control (Git), and the ability to apply software development best practices to infrastructure data.
Analytical Problem Solving: A passion for debugging complex system failures and the communication skills to translate technical infrastructure health into clear narratives for cross-functional stakeholders.

Responsibilities

Engineer Resilient Data Pipelines: Design and scale automated ETL/ELT pipelines to ingest high-volume time-series metrics from thousands of global devices, ensuring 100% data integrity for critical operational decisions.
Architect Observability Frameworks: Build and maintain sophisticated visualization solutions (such as Grafana or Kibana) that translate raw data into actionable insights, empowering engineering teams to transition to a self-service troubleshooting model.
Drive Platform Reliability: Partner with SRE and Product teams to define and implement SLOs/SLIs, utilizing these metrics to proactively identify performance bottlenecks and guide high-priority development efforts.
Optimize Infrastructure Performance: Contribute to the evolution of our data storage and time-series database architecture, ensuring our data lake remains performant and scalable as our metric volume grows.