Staff Software Engineer, Ads Data Warehouse

About the role

We are looking for a Staff Software Engineer to join our Ads Data Warehouse team, which builds and evolves the core data infrastructure that powers all data-driven products and analytics across the company.

Responsibilities

• Define and drive the technical roadmap and architecture, aligning the direction with product, analytics, ML, and infrastructure needs.
• Lead the design and evolution of core data systems, including data lineage, metadata management, and data catalog systems.
• Partner with cross-functional leaders to establish data governance, access control, and compliance frameworks that ensure data integrity and regulatory alignment.
• Build and scale high-reliability systems that power both real-time and batch data workflows across Ads and analytics use cases.
• Influence engineering culture by defining best practices for data modeling, observability, and developer experience.
• Drive cross-org initiatives to improve data quality, discoverability, and system adoption.
• Mentor senior engineers and help develop technical leadership across the data and infrastructure organization.
• Act as a trusted technical advisor to product and engineering leadership on strategy and scaling challenges.

Qualifications

• Bachelor’s degree or higher in Computer Science, Engineering, or a related technical field.
• 8+ years of experience in software engineering, with a strong focus on data infrastructure, platform systems, or distributed architectures.
• Proven experience designing and scaling large-scale data platforms or data-intensive systems.
• Strong proficiency in Golang, Python, or Java.
• Deep understanding of distributed systems, metadata management, and data modeling principles.
• Hands-on experience with cloud data platforms (e.g., GCP, AWS, Azure) and data orchestration frameworks (e.g., Airflow, Beam, Dataflow, Kafka).
• Demonstrated ability to define and lead complex technical initiatives that span multiple teams or domains.
• Excellent communication skills, with the ability to influence and align stakeholders across engineering, product, and compliance.

Preferred Qualifications

• Experience leading the design and development of data governance systems at scale, such as data catalog, data lineage, and/or data asset management.
• Expertise in data governance, access control, and privacy compliance frameworks (e.g., GDPR, CCPA).
• Deep understanding of metadata-driven architectures, data quality frameworks, and observability systems.
• Proven ability to set long-term technical direction, guide multiple teams through architectural transitions, and drive platform adoption.
• Recognized for technical mentorship, thought leadership, and fostering a culture of excellence in data infrastructure engineering.