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Strong brand, metro location, mid-level generalist data role with broad tooling increases competition.
Core data engineering skills are transferable across industries, though advertising domain experience is a plus.
Multiple mandatory technical skills and an explicit 5+ years requirement raise filter strictness.
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Design, build, and maintain scalable big data infrastructure and pipelines processing billions of events daily.
Ensure data quality and optimize platform performance across multiple cloud and big data technologies.
Collaborate with product and engineering teams for roadmap alignment and deliver technically feasible solutions to drive revenue and improve customer experience.
Bachelor's degree in Computer Science or related technical discipline.
5+ years experience designing and developing big data processing systems using distributed computing.
1+ years production experience with modern cloud data warehouses like Snowflake and advanced dbt workflows.
Proficient in Python, Spark (PySpark), SQL optimization, NoSQL databases (DynamoDB, MongoDB), Airflow, AWS cloud platform, and object-oriented programming (e.g., Java).
Experienced working with large-scale, complex data engineering projects involving diverse data sources and high event volumes.
Comfortable leading technical discussions and aligning cross-functional teams on data platform roadmaps and implementations.
Tech-savvy with strong skills in cloud-native architectures, big data technologies, and continuous learning of emerging tools like Spark and Kubernetes.