Senior Data Engineer

Role overview A senior or lead data engineering position focused on designing, building, and operating the machine learning and data infrastructure that powers advertising applications. The work spans ML pipelines, traditional data pipelines, and supporting data stores, all delivered inside an engineer-led continuous deployment environment with a strong emphasis on testing and quality.

Responsibilities - Design and implement scalable Spark and Python code that powers ML and data pipelines used by advertising products. - Apply data structures and algorithms thoughtfully, optimizing for performance and correctness across data stores. - Collaborate with product and design stakeholders to translate business needs into pipeline and architecture solutions. - Build data architecture with attention to scalability, reliability, and privacy preservation. - Maintain unit tests and code coverage, targeting continuous releases with a low defect rate. - Contribute to CI, pull request reviews, prototyping, and ticket tracking to move work from idea to production.

Requirements - 5+ years of professional data engineering experience for the senior level, or 7+ years with demonstrated technical leadership for the lead level. - Bachelor's degree in computer science, mathematics, or a related STEM field, or equivalent practical experience. - Hands-on experience building data pipelines with Apache Spark and deploying machine learning models. - Proficiency in Python plus at least one of Go, C, C++, C#, or Java. - Track record of writing clean, well-tested code and learning new languages or tools quickly. - Experience mentoring teammates, leading meetings, and partnering with product owners, analysts, and designers to scope work.

Nice to have - Prior experience in adtech, marketing technology, or another data-intensive product environment.