Want to know if this job is worth applying to?
Lehi, Utah, United States
Onsite
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.
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.
Project Execution: The data platform evolves into an open-source, scalable, self-service environment that is fully adopted by engineering teams across the company.
System Impact: Measurable improvements in system latency, throughput, and cost-efficiency for production-critical workloads.
Team Impact: Measurable increase in developer velocity across the organization, driven by the removal of architectural friction and support of AI tools.
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 the broader Engineering and Product leadership.
Role as the primary technical authority on scalability and distributed systems for the entire organization.
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.
This role reports directly to the Chief Technology Officer (CTO).
You will be joining a growing team of 50+ professionals across global locations.
In this role, 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.
Recruiter Interview
Technical/Architectural Deep Dive Interview
Interview with Engineering Leadership
Reference Checks
Executive Review
Offer
The "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.