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Mid-level data engineer in Bengaluru with common big-data stack and generic SDE title increases competition.
Core data engineering skills (Spark, Kafka, SQL) are highly transferable across industries.
Explicit 4+ years and mandatory big-data, streaming, and coding skills create strict screening criteria.
Design, build, and operate scalable, fault-tolerant data platforms, pipelines, and services powering analytics, engineering, and Data Science.
Own end-to-end modules within the Data Engineering platform including system design, implementation, and production operations.
Continuously monitor and improve performance, scalability, reliability, and operational efficiency of large-scale data infrastructure.
4+ years of experience in Data Engineering, Software Engineering, or related technical field.
Strong experience with big data technologies like Hadoop, Spark, Hive, or Presto, and streaming platforms such as Kafka, Kinesis, or RabbitMQ.
Proficiency in at least one programming language such as Python, Java, or Scala and strong SQL skills with Spark SQL, HiveQL, T-SQL, or PL/SQL.
Experience designing highly available, fault-tolerant services and working with production data systems for troubleshooting and operational excellence.
Experienced in building and operating large-scale, distributed data platforms and pipelines with attention to performance and reliability.
Skilled in collaborating cross-functionally with engineering, analytics, Data Science, and business teams to translate complex data requirements into scalable solutions.
Comfortable working in a fast-paced, high-growth, technology-focused environment with hands-on production system development and problem-solving.