Senior Software Engineer, Ads Data Warehouse

About the Role:

We are looking for a Senior Software Engineer to join our Ads Data Warehouse team, responsible for designing and maintaining the data infrastructure that powers our Ads product. In this role, you will build scalable, reliable, and high-performance data pipelines and systems that enable accurate reporting, billing, and analytics for advertisers. You will work closely with product managers and data scientists to ensure that data pipelines and storage systems are robust, efficient, and future-proof.

Responsibilities:

• Design, implement, and maintain scalable data pipelines, ETL processes, and data warehouse schemas for Ads data.
• Build and optimize systems for large-scale data ingestion, transformation, and aggregation to support real-time and batch analytics.
• Collaborate with product and data scientist teams to ensure data accuracy, consistency, and reliability across all Ads metrics and reports.
• Partner with data scientists and analysts to design data models that support experimentation, machine learning, and insights generation.
• Continuously improve data performance and reliability through monitoring, automation, and testing.
• Mentor junior engineers and contribute to establishing best practices for data engineering and warehousing.

Qualifications:

• Bachelor Degree or higher in Computer Science or equivalent technical degree
• 4+ years of experience in software engineering, with a strong focus on data-intensive systems.
• Proficiency in at least one programming language such as Python, Golang, or Java.
• Deep understanding of data modeling, ETL design, and data warehouse architecture.
• Experience with distributed data processing systems and data storage technologies.
• Strong problem-solving skills and ability to write clean, maintainable, and efficient code.
• Excellent collaboration and communication skills, with experience working across cross-functional teams.

Preferred Qualifications:

• Experience leading the development of product data pipelines and backend services at scale for reporting, billing, and business intelligence.
• Familiarity with streaming data architectures and analytics.
• Hands-on experience with cloud data platforms (e.g., GCP, AWS, Azure) and infrastructure-as-code tools (e.g., Terraform).
• Demonstrated experience in optimizing query performance and large-scale data systems.
• Track record of leading complex data infrastructure projects end-to-end.