Senior Software Engineer - Applied Data - Moloco Ads

Moloco • Seattle, WA

3d • $184,000 - $230,000

About The Position

The Ads Applied Data team builds and scales the foundational data infrastructure that powers Moloco’s advertising platform. As a Senior Software Engineer, you will design, develop, and optimize distributed data systems for real-time and batch processing, ensuring reliable and low-latency delivery of data across the ads ecosystem. You’ll work closely with Product, ML, and Data Science teams to enable feature engineering, identity resolution, and advanced user signal enrichment across online and offline pipelines.

Requirements

• Bachelor’s or Master’s degree in Computer Science, or equivalent technical field.
• 5+ years of software engineering experience with one or more modern languages (Java, Kotlin, Go, C++, C#, or Python).
• Proven experience designing and building large-scale distributed systems and backend services.
• Hands-on experience with data processing frameworks such as Apache Beam, Dataflow, or Spark, and orchestration tools like Airflow.
• Strong understanding of cloud infrastructure (GCP, AWS, or Azure) and data storage technologies (BigQuery, Bigtable, Redis, GCS, Kafka, Pub/Sub).
• Demonstrated experience delivering impactful projects through collaboration with cross-functional teams (Product, ML, Data Science).

Nice To Haves

• Experience with Feature Infra / Feature Store architecture and operations.
• Experience in Identity Graph design and construction to enhance user signal quality.
• Deep familiarity with AdTech or Machine Learning infrastructure domains.
• Experience working with Petabyte-scale data and high-availability systems.

Responsibilities

• Design and build large-scale distributed systems for data ingestion (Petabyte-scale), transformation, and serving.
• Partner with ML and Serving teams to support feature engineering workflows, connecting offline data to serving systems.
• Contribute to the evolution of Feature Infra / Feature Store, ensuring scalability, discoverability, and consistency of feature data.
• Collaborate on Identity Graph construction to unify user and device identifiers for more effective signal enrichment and targeting.
• Improve system observability, resilience, and performance in high-throughput, low-latency environments.
• Mentor engineers and help define best practices for data and backend engineering.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees