Staff Data Engineer

onX • Bozeman, MT

1d • Hybrid

About The Position

The Staff Data Engineer is a senior leader responsible for designing and evolving core components of onX’s lakehouse and data platform. This role focuses on how data is structured, governed, secured, and described so that analytics, product features, and AI systems can operate reliably at scale.
This engineer operates at the intersection of data architecture, metadata, governance, and security, leading complex initiatives and setting technical direction within the Data Engineering organization. They are a trusted technical partner to Product, Analytics, Data Science, Security, and Platform teams, and serve as a force multiplier for other engineers through high-level technical guidance and active mentorship.
As an onX Data Engineer, your day to day responsibilities would look like:
Technical Leadership & Architecture
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.
Metadata, Governance & Open Standards
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.
Security, Access Control & Compliance
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.
Platform Reliability & Operations
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.
Organizational Impact & Collaboration
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.

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.

Benefits

• Competitive salaries, annual bonuses, equity, and opportunities for growth
• Comprehensive health benefits including a no-monthly-cost medical plan
• Parental leave plan of 5 or 13 weeks fully paid
• 401k matching at 100% for the first 3% you save and 50% from 3-5%
• Company-wide outdoor adventures and amazing outdoor industry perks
• Annual “Get Out, Get Active” funds to fuel your active lifestyle in and outside of the gym
• Flexible time away package that includes PTO, STO, VTO, and 7 paid holidays annually

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level