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Strong employer brand, metro location, and widely-available data engineering skillset increase competition.
Core data engineering skills are transferable, though advertising domain and privacy needs add some specificity.
Explicit 10+ years requirement and specific big-data tech stack make filtering strict.
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Design, develop, and maintain large-scale data pipelines and ETL workflows using Apache Spark and Apache Airflow.
Optimize and monitor high-scale data processing systems ensuring reliability, scalability, and minimal downtime.
Collaborate across teams to deliver integrated data engineering solutions and provide mentorship to junior engineers, incorporating AI-augmented engineering practices responsibly.
10+ years of experience in software and/or data engineering with expertise in big data technologies like Apache Spark and Apache Airflow.
Bachelor’s degree in computer science, Engineering, or related field (or equivalent experience).
Advanced SQL skills with expertise in query optimization for large datasets.
Hybrid work model requiring in-office presence Monday through Thursday; Fridays flexible remote unless otherwise required.
Experienced in building and optimizing distributed data processing and real-time data pipelines at scale.
Strong technical foundation in distributed systems architecture and software engineering principles (SOLID).
Comfortable working proactively in a cross-functional, hybrid environment with a focus on high-quality data services and responsible AI implementation.