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Strong Tier-1 brand, metro location, mid-level generalist title, and broad skillset make competition high.
Core data engineering skills are transferable across industries, though retail domain experience is preferred.
Explicit 5+ years and mandatory Spark/Scala/BigQuery expertise indicate high shortlisting strictness.
Design, develop, and maintain scalable data pipelines and data processing frameworks using Apache Spark, Scala, and Google BigQuery.
Optimize data models and workloads for performance, scalability, reliability, and cloud cost efficiency in a large-scale data platform environment.
Collaborate with cross-functional teams to deliver high-quality data products and participate in architecture and design decisions involving data platforms and cloud technologies.
Bachelor's degree in Computer Science, Engineering, Information Technology, or equivalent practical experience.
5+ years of experience in software or data engineering with significant experience in building and supporting large-scale data platforms.
Strong hands-on experience with Apache Spark, Scala, Google BigQuery, Big Data/Distributed Processing, ETL/ELT, and strong SQL skills.
Experience with cloud-based data platforms, preferably Google Cloud Platform (GCP).
Experienced in designing and optimizing high-volume, high-performance data pipelines with a strong understanding of distributed computing concepts.
Comfortable participating in architecture discussions and translating complex business requirements into scalable technical solutions.
Familiarity with AI-assisted development tools (e.g., GitHub Copilot, Claude) and exposure to cloud-native architectures and related technologies.