Principal Staff Software Engineer, Data Infrastructure

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. 

LinkedIns Data Infrastructure organization builds and operates the foundational platforms that store process and serve data across LinkedIn. The organization spans online relational databases document stores and key-value serving systems as well as offline analytical streaming batch processing and orchestration platforms. These systems power LinkedIns products and support the growing demands of AI applications at global scale.

We are looking for a Principal Staff Software Engineer with deep expertise in database internals relational database performance and large-scale distributed systems. This role will lead database performance and efficiency optimization with an initial emphasis on relational systems and an opportunity to extend that work across online and offline data platforms.

You will work on query planning and execution indexing storage efficiency and application access patterns to improve performance and make better use of LinkedIns infrastructure. The ideal candidate brings a deep understanding of online transactional databases and can apply that expertise to offline analytical systems and the convergence of these architectures including query federation and hybrid transactional and analytical processing (HTAP).

This is a highly technical leadership role for a hands-on builder who can set direction and drive implementation across multiple teams. You will partner closely with database data platform and application engineers engage directly with code and design decisions and turn optimization opportunities into production improvements with company-level impact.

Responsibilities

• Set technical direction for database performance and efficiency optimization across LinkedIns online and offline data infrastructure.
• Lead improvements to database and offline systems including query planning and execution indexing storage and application access patterns.
• Diagnose performance bottlenecks across application database and storage layers and drive improvements in latency throughput resource utilization and infrastructure cost.
• Extend optimization approaches across offline analytical nearline streaming and batch systems identifying opportunities to improve query execution and storage efficiency.
• Shape architectures that connect online transactional and offline analytical systems including query federation and converged data platforms.
• Remain hands-on through code and design reviews performance investigations and proofs of concept that validate technical approaches.
• Make architectural tradeoffs across performance consistency availability reliability scalability and cost.
• Partner with platform and application teams to translate workload requirements into efficient data access and execution patterns including emerging AI workloads.
• Lead initiatives across teams from problem identification and design through implementation production rollout and adoption.
• Mentor senior engineers and strengthen engineering practices for database design performance analysis and optimization.

Qualifications :

Basic Qualifications

• BA/BS degree in Computer Science or a related technical field or equivalent practical experience.
• 10 years of industry experience in software engineering database systems distributed systems or related infrastructure areas.
• 5 years of experience in an architect technical lead or senior technical leadership capacity driving architecture and technical direction across complex systems or multiple engineering teams.
• Experience designing building or optimizing production database systems including relational databases query execution indexing or storage components.
• Experience diagnosing and improving database or distributed system performance through changes to query execution storage or application access patterns.
• Hands-on programming experience and experience leading technically complex initiatives across team or organizational boundaries.

Preferred Qualifications

• Masters or PhD in Computer Science or a related technical field with experience operating at Principal Staff or equivalent scope.
• Deep expertise in database internals including query optimizers execution engines indexing storage engines and consistency and availability tradeoffs.
• Experience spanning online transactional databases and offline analytical systems including query federation HTAP or relational interfaces over data lake storage.
• A track record of delivering measurable improvements in performance hardware utilization or infrastructure cost across large production data platforms.
• Experience building or optimizing relational and distributed database platforms such as MySQL PostgreSQL TiDB or comparable systems.
• Experience with the internals or performance optimization of analytical streaming or batch processing platforms such as Spark Flink or comparable systems.
• Understanding of the performance and storage implications of AI-oriented workloads including vector embeddings text search and inference-related operations.
• Demonstrated ability to set technical strategy align senior engineers and leaders and drive implementation and adoption across multiple teams while remaining hands-on.

Suggested Skills

• Database Systems
• Database Performance Optimization
• Distributed Systems
• Technical Strategy

LinkedIn is committed to fair and equitable compensation practices.    

The pay range for this role is $231000 to $378000. Actual compensation packages are based on several factors that are unique to each candidate including but not limited to skill set depth of experience certifications and specific work location. This may be different in other locations due to differences in the cost of labor.    

The total compensation package for this position may also include annual performance bonus stock benefits and/or other applicable incentive compensation plans. For more information visit Information :

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No

Employment Type :

Full-time