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Mid-level data engineer, popular Java+Spark skillset, and metro location drive high candidate competition.
Core data engineering skills (Spark, Java, cloud) are highly transferable across industries.
Explicit 3+ years plus mandatory Java, Spark, cloud, and CI/CD skills create strict technical filtering.
Translate architectural roadmaps into scalable, production-ready data solutions accelerating cloud migration.
Design, develop, and maintain high-performance batch and real-time data pipelines using Java and Apache Spark.
Optimize data processing performance and cloud costs while collaborating with cross-functional teams to align deliverables with business objectives.
3+ years in software or data engineering with experience in large-scale, production-grade data processing applications.
Advanced proficiency in Java and hands-on experience with Apache Spark and Hadoop for distributed data processing.
Experience designing and deploying data solutions on major cloud platforms such as AWS or GCP.
Hybrid work model requiring minimum two days per week in-office presence (specific to location).
Experienced in modernizing legacy on-premises batch workloads to cloud-native or event-driven architectures.
Skilled at implementing CI/CD pipelines, test automation frameworks, and Infrastructure as Code.
Able to work independently in an Agile environment, balancing multiple priorities and delivering high-quality outcomes.