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Tier-1 employer, metro location, and broad data engineering skillset create moderate candidate competition.
Data engineering skills are transferable across industries but require specific tooling and architecture experience.
Explicit 10+ years and multiple required technologies (Java, Kafka, Snowflake) raise shortlisting strictness.
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Design, build, deploy, and operate scalable data architecture and software solutions handling structured and unstructured data from multiple sources.
Develop, maintain, and optimize data pipelines, ensuring data quality, security, and compliance for high-volume environments.
Collaborate with data scientists and business teams to analyze complex datasets, support feature engineering, and create reporting/visualizations linking data to business outcomes.
10+ years professional experience in software application design and development.
Degree in B.Tech, BE, ME, MTech, MCA, MS in CS, IT, MIS or equivalent.
Strong experience with Java Microservices, Spring Boot, Kafka, Zookeeper, Apache Solr, Oracle (RDBMS), PL/SQL, and exposure to NoSQL, Snowflake, and big data technologies.
Familiarity with Agile and Waterfall methodologies, CI/CD pipelines (Jenkins), automated testing, and development tools including Jira and Git.
Experienced in architecting and managing complex distributed data platforms using microservices and big data tech in cloud and on-prem environments.
Able to lead moderately complex projects independently from design through deployment with strong coding and testing discipline.
Capable of integrating data engineering solutions with AI/ML processes and liaising cross-functionally to address business and compliance needs effectively.