Senior Data Engineer, Demandbase

• If you are passionate about large-scale systems, real-time data, and making a measurable impact in the AdTech space, we would love to hear from you
• 5+ years of experience as a Data Engineer or Backend Software Engineer working on distributed systems or large-scale data pipelines
• Proficiency in Python or Java, with strong software engineering fundamentals and clean coding practices
• Experience with streaming frameworks such as Apache Beam, Flink, or Spark, and messaging systems like Kafka
• Comfortable working with SQL, nested data, and analytics platforms like BigQuery
• Familiarity with cloud infrastructure (GCP preferred), Docker or Kubernetes, and CI/CD workflows
• Strong debugging and system optimization skills
• A self-starter who thrives in a collaborative, fast-paced environment

Desirable

• We are looking for a Senior Data Engineer to join our Advertising Engineering team. Our team builds and operates Demandbase’s proprietary Demand-Side Platform (DSP), one of the few B2B-specific DSPs in the world. We process over 1 million queries per second and handle tens of billions of data points daily
• As a Senior Data Engineer, you will play a key role in scaling the data pipelines and backend systems that power real-time bidding, audience targeting, and campaign measurement. This is a hands-on role for someone who thrives at the intersection of data engineering and backend infrastructure, especially in performance-critical environments
• Design and maintain streaming and batch data pipelines to support campaign optimization and real-time bidding decisions
• Collaborate with backend Go engineers to integrate data systems with the DSP’s bidding engine
• Build scalable systems across Spark, BigQuery, Airflow, and Postgres that process and enrich billions of daily events with low latency and high reliability
• Optimize the performance and cost of data workflows across Kafka, BigQuery, Aerospike, and other distributed systems
• Debug production issues, participate in code reviews, and write clean, testable, and maintainable code
• Work cross-functionally with Product, Data Science, and Engineering teams to solve business-critical problems