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Mid-level Java/Spark data engineer, metro location, strong brand and common skillset increases applicant competition.
Java, Spark, cloud and container skills are broadly transferable across industries despite nice-to-have banking experience.
Explicit 3–5 years plus mandatory Java, Spark, Kubernetes and CI/CD requirements make filters stringent.
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Design, develop, and test software components independently, ensuring adherence to software craftsmanship and Agile SDLC practices.
Collaborate with product owners to decompose customer requests into detailed stories and implement APIs and data access rules with other teams.
Perform level 2/3 production support, maintain production standards, automate repetitive tasks, and validate releases with metrics and defect reports.
3-5 years of hands-on experience with Java and Spring Boot Framework.
At least 2 years hands-on experience with Java Spark on HDInsight or SoK8s.
Experience with Container & Orchestration tools such as Docker & Kubernetes and Agile methodologies CI/CD pipelines.
Experience with at least one RDBMS: Oracle, PostgreSQL, or SQL Server.
Strong Java and Big Data engineering background, with experience implementing scalable data pipelines using Spark and container orchestration.
Experienced working in Agile teams within enterprise environments, contributing to API design and cross-team collaboration.
Competent in production support and operational maintenance, including root cause analysis and automation of common tasks.