VP of Data Platform & Architecture

About the role

Lead the data organization through directors and managers, focusing on the strategic evolution of data engineering and platform architecture. Architect and scale distributed systems capable of processing petabyte-scale datasets and hundreds of billions of events. Collaborate with cross-functional teams to drive a company-wide data vision and operating model aligned with corporate goals. Obsess over the "developer experience," building self-service capabilities and abstractions that reduce time-to-delivery from days to minutes. Manage the performance and cost efficiency of the platform, including transitions toward open-source technologies like Airflow, Debezium, Iceberg, Trino, and Spark. Mentor international engineering teams, establishing high-level frameworks for technical excellence and operational rigor.

Responsibilities

• Architect and scale distributed systems capable of processing petabyte-scale datasets and hundreds of billions of events.
• Drive a company-wide data vision and operating model aligned with corporate goals.
• Build self-service capabilities and abstractions to reduce time-to-delivery from days to minutes.
• Manage the performance and cost efficiency of the platform, including transitions to open-source technologies (e.g., Airflow, Debezium, Iceberg, Trino, Spark).
• Mentor international engineering teams to establish frameworks for technical excellence and operational rigor.

Requirements

• Scale Systems Expertise: Deep experience architecting and operating large-scale distributed data platforms at a multi-petabyte scale on cloud services (AWS preferred).
• Platform-First Mindset: Proven ability to build internal developer frameworks and abstractions rather than just managing pipelines.
• Technical Depth: Strong background in software engineering and distributed systems design, specifically with batch and real-time processing.
• Global Leadership: Experience leading and scaling international engineering organizations of 50+ professionals.
• Open-Source Fluency: Familiarity with modern open-source stacks (e.g., Airflow, Debezium, Kafka, Spark, Clickhouse) and the trade-offs involved in platform architecture.
• Data Fanaticism: A relentless focus on using data to improve system performance, cost-efficiency, and developer velocity.

What high performance looks like

• Project Execution: The data platform evolves into an open-source, scalable, self-service environment fully adopted by engineering teams.
• System Impact: Measurable improvements in system latency, throughput, and cost-efficiency for production-critical workloads.
• Team Impact: Measurable increase in developer velocity driven by the removal of architectural friction and support of AI tools.

Career Growth

• Direct influence on the technical trajectory of a global ecommerce leader.
• Opportunity to lead a high-stakes transition from commercial to open-source platform architecture.
• Executive-level networking and strategic partnership with broader Engineering and Product leadership.
• Role as the primary technical authority on scalability and distributed systems for the entire organization.

First 30, 60, 90 Days

• 30 Days: Complete a comprehensive audit of the current architecture, identify friction points in developer velocity, and build relationships with international team leads.
• 60 Days: Refine the roadmap for platform abstractions and contribute to the transition plan for key open-source components.
• 90 Days: Demonstrate early wins in system performance or cost-efficiency.

Team

This role reports directly to the Chief Technology Officer (CTO). You will join a growing team of 50+ professionals across global locations. You will collaborate closely with Directors of Data Engineering, SRE Leads, and Product Managers, as well as other departments including Engineering, Security, and Sales. This position is mentored by the CTO.

How to stand out

• Nice-to-Haves: Experience in building developer tools, familiarity with Clickhouse, and a history of contributing/managing significant open-source data projects.
• Stand-Out Tips:
  • Be prepared to discuss and articulate trade-offs across database types, streaming platforms, query engines, and orchestration tools—including commercial vs. open-source considerations at scale.
  • Highlight specific instances where you improved developer velocity by introducing platform abstractions.
  • Demonstrate your ability to lead and unify engineering teams across different time zones and cultures.

About Pattern

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, Walmart.com, Target.com, eBay, Tmall, TikTok Shop, JD, and Mercado Libre.

Pattern has been named one of the fastest-growing tech companies headquartered in North America by Deloitte and one of the 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®.

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: Pattern matches 100% of the first 3% in eligible compensation deferred and 50% of the next 2% in eligible compensation deferred.