Staff Software Engineer, Ads Data Warehouse

About Moloco:

Moloco builds some of the most powerful AI advertising solutions in the world. Our name—short for "machine learning company"—reflects our core mission: democratizing access to the advanced AI that has historically been reserved for tech giants. Led by machine learning pioneers who built some of the most successful ad systems at Google, including YouTube's monetization engine and key search advertising technologies, we're transforming how businesses grow and compete in the digital economy.

Built with AI from day one, Moloco’s planet-scale machine learning platform powers a suite of solutions for advertising growth and monetization. Moloco Ads is an AI-powered platform that delivers real business outcomes for mobile app marketers through performance-based user acquisition. Moloco Commerce Media enables retailers and marketplaces to build revenue-generating ad businesses that balance user experience and advertiser performance.

Moloco is headquartered in Silicon Valley, with offices in Seattle, New York, San Francisco, Seoul, Beijing, Singapore, Bangalore, Gurgaon, Tokyo, Shanghai, London, Tel Aviv, and Berlin.

Moloco is a truly rewarding place to work and in an exciting period of growth, which you could be a part of. Join us today and apply now!

About the Role:

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

The Data Platform team is responsible for foundational systems such as the feature store, data lineage, data catalog, access control, and compliance frameworks—enabling teams to securely and efficiently leverage data for decision-making, ML modeling, and Ads optimization.

As a Staff Engineer, you will define the technical vision and strategy for the Ads Data Platform, ensuring that our infrastructure scales to meet the growing complexity of our Ads ecosystem. You will lead architectural design, drive cross-team initiatives, and mentor engineers across teams. Your work will establish the foundation for reliable, compliant, and discoverable data across the entire company.

Responsibilities:

• Define and drive the technical roadmap and architecture for the Ads Data Platform, aligning platform direction with product, ML, and infrastructure needs.
• Lead the design and evolution of core data platform services, including feature store, 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 platform 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 platform 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 development of feature stores, data catalogs, or lineage systems at scale.
• 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,