Staff Data Platform Engineer
We are looking for a visionary Staff Data Platform Engineer to lead the design, architecture, and implementation of our next-generation data platform. In this high-impact role, you will be the catalyst that enables our partners and global teams to extract actionable insights with unprecedented speed and sustainability. If you are ready to architect the backbone of a data-driven empire and eliminate friction at a global scale, you belong at Pattern.
What is a day in the life of a Staff Data Infrastructure Engineer?
Build and maintain scalable, high-performance data infrastructure designed to support both batch and real-time use cases for a wide variety of global stakeholders
Design and implement architectural solutions that drastically reduce friction in data access across the organization.
Collaborate cross-functionally with Engineering, Data, and Product teams to align the platform with diverse technical requirements.
Understand and integrate best security practices to ensure access compliance across all data assets
Troubleshoot and resolve complex issues in distributed data systems to ensure total data integrity.
Architect and implement AI-driven diagnostic systems to autonomously identify, analyze, and resolve complex issues impacting data availability and platform health.
What will I need to thrive in this role?
8+ years of experience in data infrastructure or backend software engineering with a "Data Fanatic" mindset.
Cloud Mastery: Strong expertise in cloud environments, container orchestration, and event streaming technologies for managing large-scale infrastructure.
Data Processing: Strong experience with distributed data processing and OLAP technologies such as Spark, Trino, and ClickHouse; Snowflake or Databricks experience is a plus.
Technical Excellence: Ability to write clean, maintainable code in Python, GoLang, Java, Ruby, or C++.
Proactive Leadership: A "can-do" attitude with a proven track record of solving complex problems and taking initiative.
Collaborative Spirit: Strong ability to work across teams to deliver high-quality, high-impact results.
- System Observability: Expertise in building highly observable platforms using tools like Prometheus, Grafana, or Datadog to ensure deep visibility and proactive reliability of global systems.
What does high performance look like?
Execution & Innovation: You proactively find and implement solutions that ensure platform scalability while remaining cost-effective, consistently optimizing infrastructure performance.
System Scalability: You successfully deliver major infrastructure upgrades that empower the company to harness 46+ trillion data points effectively.
A Team of Doers: You mentor team members daily, driving a culture of technical excellence and growth.
Setting the Bar: You establish and enforce industry-leading best practices, ensuring the team adopts cutting-edge processes.
What is my potential for career growth?
Direct mentorship opportunities with senior leadership in Data and Architecture.
Professional exposure through collaboration with diverse departments across the global Pattern ecosystem.
A clear, merit-based path for advancement within a rapidly growing tech company.
Opportunities to lead high-visibility projects that define the future of Pattern’s technical roadmap.
Internal promotion priority for high-performing "Pattern People."
What does success look like in the first 30, 60, 90 days?
First 30 Days: Build context quickly, assess the current platform, and identify the most important opportunities for improvement.
First 60 Days: Contribute immediately to high-priority initiatives and lead design efforts to improve platform reliability, scalability, and operations.
First 90 Days: Deliver significant technical impact, shape the platform roadmap, and provide technical leadership across the organization.
What is the team like?
This role reports directly to the VP of Data and Architecture. You will be joining a growing team of data professionals. In this role, you will collaborate closely with Data Engineers and Software Engineers as well as other departments including Engineering, Product, and Marketing. This position is mentored by the VP of Data and Architecture.
Sounds great! What’s the company culture?
Game Changers- A game changer is someone who looks at problems with an open mind and shares new ideas with team members, regularly reassesses existing plans and attaches a realistic timeline to goals, makes profitable, productive, and innovative contributions, and actively pursues improvements to Pattern’s processes and outcomes.
Data Fanatics- A data fanatic is someone who recognizes problems and seeks to understand them through data, draws unbiased conclusions based on data that lead to actionable solutions, and continues to track the effects of the solutions using data.
Partner Obsessed- An individual who is partner obsessed clearly explains the status of projects to partners and relies on constructive feedback, actively listens to partner’s expectations, and delivers results that exceed them, prioritizes the needs of your partners, and takes the time to create a personable experience for those interacting with Pattern.
Team of Doers- Someone who is a part of a team of doers uplifts team members and recognizes their specific contributions, takes initiative to help in any circumstance, actively contributes to supporting improvements, and holds themselves accountable to the team as well as to partners.
We are looking for individuals who are:
What is the hiring process?
Initial interview with Pattern’s talent acquisition team
Technical video interview with a senior member of the data platform team
Onsite interview with peers and senior leadership
Professional reference checks
Executive review
Offer
How can I stand out as an applicant?
Strong Nice-to-Haves: Expertise in Databricks/Snowflake, experience with GoLang or Scala, and a history of contributing to open-source data projects.
Quantify Success: During the interview, discuss professional accomplishments using specific data and metrics to show your impact.
Show Your Passion: Highlight any side projects related to data analytics or large-scale infrastructure.
The "Partner" Lens: Be prepared to explain how your technical decisions directly improve the experience and success of the partners who rely on your data platform.