Senior Technical Lead

About the role

We are seeking a highly skilled Hadoop Technical Lead to provide technical leadership and expertise within our Hadoop environment, specifically focused on data management and analysis.

Responsibilities

• Own the overall Hadoop platform architecture, design, and operational strategy
• Act as the technical escalation (L3) for complex production issues and performance bottlenecks
• Provide architecture-level guidance on Hadoop ecosystem components and integrations
• Lead platform assessments, optimization initiatives, and continuous improvement
• Design and enforce best practices for cluster configuration, resource management, and data layout
• Plan and execute Hadoop version upgrades, patching, and distribution migrations
• Ensure compliance with enterprise security, audit, and data governance policies
• Establish proactive monitoring, ing, and observability mechanisms
• Work closely with Data Engineers, BI teams, Application teams, and Infrastructure teams
• Participate in design reviews, CABs, and technical governance forums
• Translate business requirements into scalable technical solutions
• Provide technical guidance and support for Hadoop-related projects, ensuring best practices are followed
• Collaborate with cross-functional teams to gather requirements and translate them into technical specifications
• Optimize and maintain Hadoop clusters, ensuring high availability and performance
• Implement and manage data ingestion processes using tools such as Flume and Kafka
• Utilize HDFS, MapReduce, Hive, Impala, HBase, and Spark/Spark Streaming for data processing and analysis
• Monitor and troubleshoot Hadoop ecosystem components, ensuring system reliability and efficiency
• Stay updated with the latest trends and advancements in Big Data technologies and recommend improvements
• Document architecture designs, processes, and best practices for future reference

Requirements

• Strong knowledge and experience as a Hadoop Architecture and Internals
• Proficiency in HDFS, MapReduce, Hive, Impala, HBase, Flume, ZooKeeper, Spark/Spark Streaming, and Kafka
• Deep understanding of the Hadoop ecosystem and its components
• Experience in designing and implementing scalable data architectures
• Strong analytical and problem-solving skills
• Excellent communication and collaboration abilities
• Cluster monitoring, troubleshooting, and performance tuning
• Security implementation in Hadoop ecosystems

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field
• Relevant certifications in Hadoop or Big Data technologies are a plus