Principal Staff Software Engineer - Data Infrastructure & Data Quality

LinkedIn is seeking a visionary Principal Staff Software Engineer to lead their Data Management organization in building world-class solutions for data discovery, observability, and quality. This role represents a unique opportunity to shape the future of how data is discovered, trusted, and managed at scale.

The position combines deep technical expertise in data infrastructure and distributed systems with strategic leadership responsibilities. The successful candidate will be responsible for architecting and implementing scalable systems that handle metadata, data quality signals, and observability while setting the technical direction for the entire organization.

This is a hybrid role, allowing for a balance of remote work and office collaboration. The compensation package is competitive, ranging from $207,000 to $340,000, plus additional benefits including stock options and annual performance bonuses.

Key responsibilities include defining the technical vision for data discovery and quality, designing scalable systems, evaluating new technologies, mentoring team members, and driving operational excellence. The ideal candidate will have 10+ years of software design experience, with at least 5 years in technical leadership, and deep expertise in data platforms, quality, and observability.

LinkedIn offers a collaborative environment where you'll work with cross-functional teams to solve complex challenges in data management. The company's global reach and impact on the professional world make this an exciting opportunity to influence how millions of professionals discover and leverage data-driven insights.

The role combines technical depth with strategic thinking, requiring someone who can both architect complex systems and communicate effectively with various stakeholders. You'll be at the forefront of innovation in data infrastructure, working with cutting-edge technologies while helping shape the future of professional networking and data discovery at scale.