Senior Data Engineer

- Architect and optimize distributed data processing pipelines leveraging PySpark for high-throughput, low-latency workloads.
- Utilize the Apache big data stack (Hadoop, Hive, HDFS) to orchestrate ingestion, transformation, and governance of massive datasets.- Engineer fault-tolerant, production-grade ETL frameworks ensuring seamless scalability and system resilience.- Interface cross-functionally with Data Scientists and domain experts to translate analytical needs into performant data solutions.- Enforce rigorous data quality controls and lineage mechanisms to uphold auditability and regulatory compliance.- Contribute to core architectural design, implement clean and modular Python/Java code, and drive performance benchmarking at scale.Required Skills :- 5-7 years of experience.- Strong hands-on experience with PySpark for distributed data processing.- Deep understanding of Apache ecosystem (Hadoop, Hive, Spark, HDFS, etc.)- Solid grasp of data warehousing, ETL principles, and data modeling.- Experience working with large-scale datasets and performance optimization.- Familiarity with SQL and NoSQL databases.- Proficiency in Python and basic to intermediate knowledge of Java.- Experience in using version control tools like Git and CI/CD pipelines.Nice-to-Have Skills :- Working experience with Apache NiFi for data flow orchestration.- Experience in building real-time streaming data pipelines.- Knowledge of cloud platforms like AWS, Azure, or GCP.- Familiarity with containerization tools like Docker or orchestration tools like Kubernetes.If you are interested in the above roles and responsibilities, please share your updated resume along with the following details :Name as per Aadhar card.:Mobile Number :Alternative Mobile :Mail ID :Alternative Mail ID :

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