Principal Staff Software Engineer - Data Lake Infrastructure

This role will be based in Mountain View or Bellevue.

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

The Data Lake Infrastructure team builds and operates the foundational storage and table-management technologies powering LinkedIn's data platform at massive scale. We own OpenHouse, LinkedIn's open-source control plane for Apache Iceberg tables, along with the broader data lake stack (storage engines, table formats, metadata/catalog services, and compaction/retention systems) that serves thousands of internal teams, petabyte-scale datasets, and mission-critical analytics, ML, and AI workloads. We collaborate closely with open-source communities (Apache Iceberg, Trino, Spark) and partner teams across Data Infrastructure, Analytics, and AI Platform to ensure reliable, cost-efficient, and governable data access company-wide.

We are seeking a Principal Technical Lead to drive the technical vision and execution for OpenHouse and LinkedIn's data lake technologies. You will set architectural direction, lead complex cross-team initiatives, and mentor engineers building the next generation of table-management and lakehouse infrastructure. This role combines deep hands-on engineering with technical leadership — you'll design for scale, reliability, and openness while representing LinkedIn in the broader open-source data lake ecosystem.

Come join our infrastructure teams and share the knowledge with a broader community while making a real impact within our company.

Core Responsibilities:

• Own the technical roadmap and architecture for OpenHouse and core data lake services (catalog, table format, compaction, retention, replication, governance).
• Lead design and implementation of large-scale, highly available distributed systems handling petabyte-scale Iceberg tables.
• Drive open-source contributions and engagement with Apache Iceberg and related ecosystem projects.
• Partner with Analytics, AI Platform, and Data Infra teams to align on requirements, integration points, and long-term platform strategy.
• Provide technical mentorship and code/design review leadership across the team; raise the engineering bar.
• Evaluate and adopt emerging lakehouse technologies, driving build-vs-adopt decisions.
• Ensure system reliability, performance, and cost efficiency through sound SLOs, monitoring, and capacity planning.
• Lead technical design reviews, write RFCs/design docs, and drive consensus across stakeholders.
• Guide incident response and root-cause analysis for critical data lake infrastructure issues.
• Guide incident response and root-cause analysis for critical data lake infrastructure issues.

Department: Engineering
Experience Level: Director