Senior Data Platform Engineer

Are you obsessed with data, partner success, taking action, and changing the game? If you have a whole lot of hustle and a touch of nerd, come work with Pattern! We want you to use your skills to push one of the fastest-growing companies headquartered in the US to the top of the list.

Pattern accelerates brands on global ecommerce marketplaces leveraging proprietary technology and AI. Utilizing more than 66 trillion data points, sophisticated machine learning and AI models, Pattern optimizes and automates all levers of ecommerce growth for global brands, including advertising, content management, logistics and fulfillment, pricing, forecasting and customer service. Hundreds of global brands depend on Pattern's ecommerce acceleration platform every day to drive profitable revenue growth across 60+ global marketplaces—including Amazon, , , eBay, Tmall, Tik Tok Shop, JD, and Mercado Libre.

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Pattern has been named one of the fastest growing tech companies headquartered in North America by Deloitte and one of best-led companies by Inc. We place employee experience at the center of our business model and have been recognized as one of Newsweek's Global Most Loved Workplaces®.

We are looking for a high-impact Senior Data Platform Engineer to design, scale, and optimize our high-performance data infrastructure. In this role, you will build the critical systems that enable our internal teams and global partners to process and query trillions of data points with speed and reliability. If you are ready to eliminate data friction, build cutting-edge platform solutions, and thrive in a fast-paced environment, you belong at Pattern!

• Design, build, and operate scalable, high-performance data infrastructure supporting both batch and real-time processing on a modern open-source stack:
  Iceberg, Spark, Kafka, etc.

• Take a vague or high-level problem statement, drive it to a concrete architecture, and ship it to production end to end.

• Define and manage platform infrastructure as code, and build the self-healing, observable systems that keep it reliable without manual intervention.

• Build the tooling, SDKs, and self-service paths that let Data Engineers, Software Engineers, and AI agents use the platform safely without asking for help.

• Implement optimized data pipeline architectures and data access patterns that eliminate friction across global teams.

• Collaborate cross-functionally with Software Engineers, Data Engineers, and Product teams to meet evolving technical requirements, and bring a strong point of view to design reviews.

• Integrate cloud security and access control best practices across all distributed data assets.

• Troubleshoot, debug, and resolve complex performance bottlenecks in distributed data systems to ensure platform uptime and data integrity.

• Build diagnostic and monitoring tools to proactively identify and resolve issues affecting system health and data availability.

• 4+ years of experience in data platform engineering, data infrastructure, or backend software development with a "Data Fanatic" mindset.

• End-to-End Problem Solving in Ambiguity: Ability to take vague or high-level requirements and drive them to a concrete, production-ready solution. You must have a track record of navigating complex technical roadblocks independently and architecting systems that solve the "whole" problem, not just the immediate ticket.

• Software Engineering: Strong proficiency in building performant, concurrent data services and platform tooling. Go is preferred, but deep expertise in Java, Python, Ruby, or Scala is accepted.

• Modern Open-Source Architecture: Deep hands-on experience designing and operating modern data stacks. You should be comfortable with solutions involving Apache Iceberg, Glue catalog, and S3 for storage;
  Trino, Spark, and Click House for compute; and Kafka for streaming, specifically within a Kubernetes environment.

• SRE Mindset & Infrastructure as Code: Apply Dev Ops and Site Reliability Engineering principles to data infrastructure. You must be proficient in defining…