Synechron is a leading digital consulting firm with 17,000+ collaborative employees in 55+ global offices across 17+ countries.
From our solid financial services industry foundation, we have become a prominent global digital consulting firm for large financial services and technology firms.
With a key focus on trust, and in partnership with our clients, we’re leading modernization and digital optimization journeys with expertise that spans Consulting, Data, Design, Cloud and Engineering across various industries.
We can provide you with customized end-to-end solutions that drive business value.

We are looking for a highly skilled and motivated Data Engineer – PySpark & Cloudera CDP to join our data engineering team. The successful candidate will be responsible for designing, developing, and maintaining scalable data pipelines that ensure high data quality, reliability, and availability across the organization.
The ideal candidate will have solid experience with PySpark, Apache Spark, the Cloudera Data Platform (CDP), Python, SQL, and distributed data processing technologies.



Experience with cloud-native tools and modern data engineering practices will be an added advantage.

Job Description:
Responsibilities:
- Design, develop, test, and maintain scalable data pipelines using PySpark, Apache Spark, Python, and SQL.
- Build and optimize ETL/ELT processes for structured and unstructured data.
- Develop data processing solutions using the Cloudera Data Platform and related big data technologies.
- Work with distributed storage and processing technologies such as HDFS, Hive, Impala, Kafka, and Spark.
- Implement data quality checks, validation rules, reconciliation processes, and monitoring capabilities.
- Optimize Spark jobs and data pipelines through efficient partitioning, joins, caching, resource utilization, and query optimization.
- Troubleshoot data pipeline failures, performance issues, data inconsistencies, and production incidents.
- Collaborate with data ar

📌 Data Engineer (Chennai)
🏢 Synechron
📍 Chennai