▷ 15h Left: Platform Engineer

4 days ago

Vadodara Rajkot Surat, India Tata Electronics Tepl Full time

Job Description Job Responsibilities - - Architect and implement a scalable, offline Data Lake for structured, semi-structured, and unstructured data in an on-premises, air-gapped environment. - Collaborate with Data Engineers, Factory IT, and Edge Device teams to enable seamless data ingestion and retrieval across the platform. - Integrate with upstream systems like MES, SCADA, and process tools to capture high-frequency manufacturing data efficiently. - Monitor and maintain system health, including compute resources, storage arrays, disk I/O, memory usage, and network throughput. - Optimize Data Lake performance via partitioning, deduplication, compression (Parquet/ORC), and implementing effective indexing strategies. - Select, integrate, and maintain tools like Apache Hadoop, Spark, Hive, HBase, and custom ETL pipelines suitable for offline deployment. - Build custom ETL workflows for bulk and incremental data ingestion using Python, Spark, and shell scripting. - Implement data governance policies covering access control, retention periods, and archival procedures with security and compliance in mind. - Establish and test backup, failover, and disaster recovery protocols specifically designed for offline environments. - Document architecture designs, optimization routines, job schedules, and standard operating procedures (SOPs) for platform maintenance. - Conduct root cause analysis for hardware failures, system outages, or data integrity issues. - Drive system scalability planning for multi-fab or multi-site future expansions. Essential Attributes (Tech-Stacks) - - Hands-on experience designing and maintaining offline or air-gapped Data Lake environments. - Deep understanding of Hadoop ecosystem tools: HDFS, Hive, Map-Reduce, HBase, YARN, zookeeper and Spark. - Expertise in custom ETL design, large-scale batch and stream data ingestion. - Strong scripting and automation capabilities using Bash and Python. - Familiarity with data compression formats (ORC, Parquet) and ingestion frameworks (e.g., Flume). - Working knowledge of message queues such as Kafka or RabbitMQ, with focus on integration logic. - Proven experience in system performance tuning, storage efficiency, and resource optimization. Qualifications- - BE/ ME in Computer science, Machine Learning, Electronics Engineering, Applied mathematics, Statistics. Desired Experience Level - - 4 Years relevant experience post Bachelors - 2 Years relevant experience post Masters - Experience with semiconductor industry is a plus

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