Software Engineer, Ads Data Warehouse

Moloco • Seattle, WA

4d

About The Position

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

Requirements

• Bachelor's Degree or higher in Computer Science or equivalent technical degree
• 2+ 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.

Nice To Haves

• Experience with Ads systems and data pipelines.
• 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).
• Experience in optimizing query performance and managing large-scale data systems.

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 both real-time and batch analytics.
• Collaborate with product and data science teams to ensure data accuracy, consistency, and reliability across Ads metrics and reports.
• Work with data scientists and analysts to design data models that support experimentation, machine learning, and insights generation.
• Continuously improve data performance, reliability, and developer efficiency through monitoring, automation, and testing.
• Contribute to defining best practices for data engineering and warehousing within the team.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level