Staff Data Engineer

onX is a technology company building products that help people confidently explore the outdoors. The Staff Data Engineer will design and evolve core components of the lakehouse and data platform, focusing on data architecture, metadata, governance, security, and reliability. The role leads complex initiatives, sets technical direction, collaborates across teams, and mentors engineers.

Responsibilities:

• Design and evolve the Iceberg-based lakehouse architecture to balance scalability, cost, performance, and maintainability
• Define and promote standards for table design, partitioning, schema evolution, optimization, and data layout
• Lead architectural efforts spanning batch, streaming, and event-driven data processing where they deliver business value
• Drive the design and delivery of complex, cross-team initiatives, enabling teams to move independently within established architectural guidance
• Build vs. Buy: Evaluate and integrate technologies
• Define how datasets, pipelines, features, and models are described, related, and governed using shared metadata
• Lead the adoption and integration of open-source metadata and catalog tools (e.g., OpenMetadata or similar ecosystems)
• Establish metadata standards that enable self-service analytics, governance, and AI readiness
• Partner with BI and Analytics to ensure domain models are clearly documented and aligned to business language
• Collaborate with Data Science to ensure model inputs, features, and outputs are traceable, explainable, and reusable
• Design and evolve security and access-control models for Apache Iceberg, including table-, column-, and row-level controls
• Partner with Security and Platform teams to embed policy enforcement directly into data access paths
• Drive metadata-driven authorization patterns that scale across tools and user groups
• Ensure privacy, compliance, and regulatory requirements are incorporated into platform design
• Balance strong security guarantees with usability to support safe self-service
• Build and maintain automation for compaction, retention, lifecycle management, and cost controls
• Establish observability standards that connect pipeline health, data quality, and reliability metrics
• Provide architectural oversight during critical incidents and drive long-term 'Keep the Lights On' (KTLO) reduction
• Recommend tooling and process improvements based on industry standards and operational experience
• Align technical work with business priorities by understanding how data supports onX products and customer outcomes
• Communicate complex technical concepts clearly to engineers, product partners, and leadership
• Lead and participate in architecture and design reviews, setting a high bar for technical rigor
• Foster strong cross-team collaboration across Data Engineering, Platform, Security, Analytics, and Data Science
• Mentor senior and mid-level engineers, raising the technical bar across the team

Requirements:

• Bachelor's degree in Computer Science or equivalent experience
• Deep industry experience (typically 12+ years) building and operating large-scale data systems
• Deep expertise in distributed data systems and data architecture
• Strong experience with Apache Iceberg and similar table formats (Delta Lake, Hudi)
• Proven experience designing secure and governed data platforms
• Expertise in Python, SQL, and orchestration patterns (e.g., Airflow)
• Experience working with data ecosystems, including metadata, catalog, or governance tooling
• Strong written and verbal communication skills
• Permanent U.S. work authorization
• Deep experience in at least one major cloud environment (GCP, AWS, or Azure)
• Familiarity with cloud-native data services such as query engines, stream/batch processing systems, and object storage–based lakehouses
• Comfort with infrastructure-as-code and automated platform management