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Mid-level Big Data role, common Spark/Kafka skills, and metro Bangalore location increase applicant competition.
Core data engineering skills (Spark, Kafka, SQL) are readily transferable across industries.
Explicit 3+ years and required Spark/Java/Scala and distributed-systems skills create high shortlisting strictness.
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Design, develop, and maintain scalable data pipelines using PySpark and Apache Spark for processing large-scale structured and unstructured data.
Build real-time analytics solutions on cloud and edge devices, solving complex data and architectural challenges.
Collaborate cross-functionally with data scientists, data engineering, and firmware control teams to deliver integrated data solutions.
3+ years of relevant experience in big data engineering or related fields.
Strong programming skills in Java or Scala, with clear understanding of design patterns; Python is a bonus.
Hands-on experience with Kafka, Spark, Flink, Hadoop, or HBase internals; experience tuning and debugging Spark jobs is essential.
Qualifications: MTech or M.S. degree with emphasis in computational or decision sciences preferred; must be based in Bangalore/Mumbai, India.
Experienced in building and optimizing data pipelines and analytics in distributed environments at scale.
Demonstrates strong understanding of distributed computing principles and big data technologies including Spark and Kafka.
Comfortable working in cloud environments (AWS/GCP/Azure) with exposure to data lakes, data warehousing, SQL/NoSQL, and REST/gRPC APIs.