Senior Data Infrastructure Engineer

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!

Responsibilities

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

Requirements

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; Software Engineering: strong proficiency in building performant, concurrent data services and platform tooling, with Go preferred and deep expertise in Java, Python, Ruby, or Scala accepted; Modern Open-Source Architecture: deep hands-on experience designing and operating modern data stacks, comfortable with Apache Iceberg, Glue catalog, and S3, Trino, Spark, and ClickHouse, and Kafka for streaming within a Kubernetes environment; SRE Mindset & Infrastructure as Code: proficiency in defining infrastructure using Terraform or CloudFormation, creating self-healing systems, and setting up observability (Prometheus, Grafana, or Datadog); Database & Storage Optimization: proven ability to manage and tune relational stores (Postgres/RDS) alongside distributed systems, ensuring data consistency, efficient indexing, and optimal query performance; AI-Native Platform Thinking: comfort building a platform consumed by both humans and AI agents, exposing data and infrastructure through well-documented, programmatic interfaces (catalogs, metadata, semantic layers, MCP servers, and agent-safe query paths), and actively using AI coding tools; Opinionated Collaboration & Communication: a strong technical voice who thrives in design reviews, articulates architectural trade-offs, defends design choices with data, and professionally challenges the status quo

Nice to have

Production Go experience; Spark-on-Kubernetes operations; CDC-based ingestion (Debezium or similar); data catalog and lineage tooling; Snowflake or Databricks depth; meaningful open-source data tooling contributions

Benefits

Unlimited PTO; Paid Holidays; Onsite Fitness Center; Company Paid Life Insurance; Casual Dress Code; Competitive Pay; Health, Vision, and Dental Insurance; 401(k) match of 100% of the first 3% in eligible compensation deferred and 50% of the next 2% in eligible compensation deferred; Mentorship opportunities from engineering leadership in Data and Architecture; Broad exposure across diverse business units within Pattern's global technology organization; Clear, merit-based career path with potential advancement toward Staff Engineer or Lead Data Platform roles; Internal promotion priority for high-performing "Pattern People"