Senior Data Platform Engineer.
This mandate is run by SYMPHONI HR, a Mumbai-based executive search firm, est. 2003. Applications are email-verified and reach the search team running the role — confidentially, always.
About the organisation.
Our client is a prominent global computer software company known for its innovative solutions and commitment to technological advancement. They operate at a significant scale, serving a diverse international clientele. The company fosters a culture of continuous learning, collaboration, and excellence, empowering its employees to drive impactful change.
About the role.
We are seeking a highly skilled and self-driven Senior Data Platform Engineer to join a dynamic team. This role involves independently understanding and enhancing existing data frameworks, as well as leading modernization initiatives using cloud-native technologies. You will be instrumental in designing, developing, and maintaining scalable data ingestion and transformation frameworks, contributing significantly to the evolution of their data platforms.
What you will do.
- Design, develop, and maintain scalable data ingestion and transformation frameworks using Python, Spark, and Shell Scripting
- Independently analyze existing frameworks and implement new features and enhancements
- Drive platform modernization through cloud-native technologies, automation, and engineering best practices
- Develop optimized integrations with object storage platforms, databases, and enterprise data systems
- Build and support high-performance data pipelines on large-scale big data platforms
- Leverage AI-assisted development tools, AI agents, and LLMs to accelerate engineering productivity and solution delivery
What you bring.
- Strong hands-on expertise in Python and Apache Spark development and framework design
- Experience building reusable and scalable data ingestion and transformation frameworks
- Deep understanding of Hive, Impala, HDFS, and the Hadoop ecosystem, preferably on Cloudera-based platforms
- Strong knowledge of HDFS internals, data storage architecture, compaction strategies, partition management, resource utilization, and cluster performance optimization
- Proven ability to troubleshoot complex platform, storage, compute, and cluster-level issues, perform root cause analysis, and drive performance improvements
- Experience working with diverse database technologies and object storage platforms, with a focus on optimized connectivity and data access patterns
- Strong understanding of distributed data processing, Spark optimization, and platform engineering best practices
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