Data Engineer/Lead (Chennai)

Data Engineer Lead to design, build, and manage scalable data infrastructure and pipelines for enterprise-grade data platforms across cloud and big data ecosystems. The Ideal Candidate Will Lead a Team Of Data Engineers And Drive End-to-end Data Architecture, Ensuring High-performance, Secure, And Reliable Data Solutions That Support Analytics, AI/ML, And Business Intelligence - Lead design and development of scalable data pipelines and data engineering solutions. - Architect and implement end-to-end data platforms (batch and real-time processing). - Build and optimize ETL/ELT workflows using up-to-date data engineering tools. - Design cloud-native data solutions on AWS / Azure / GCP. - Implement data governance, data quality, and data security standards. - Collaborate with Data Scientists, Analysts, and Business stakeholders. - Manage streaming data pipelines using Kafka / real-time ingestion tools. - Monitor, troubleshoot, and optimize data systems for performance and scalability. - Lead and mentor a team of data engineers. Exp (Years) - 10 to 18 Years Required Skills - Strong experience in Python, SQL, and distributed data systems. - Expertise in Apache Spark, Hadoop, Kafka, Airflow, Databricks. - Knowledge of DevOps tools (Docker, Kubernetes, CI/CD). - Familiarity with BI tools (Power BI / Tableau). Education - B.E / B.Tech / M.Tech / MCA / M.Sc (Computer Science / IT / Data Science / Statistics) (ref:hirist.tech) Data Engineer Lead to design, build, and manage scalable data infrastructure and pipelines for enterprise-grade data platforms across cloud and big data ecosystems. The Ideal Candidate Will Lead a Team Of Data Engineers And Drive End-to-end Data Architecture, Ensuring High-performance, Secure, And Reliable Data Solutions That Support Analytics, AI/ML, And Business Intelligence - Lead design and development of scalable data pipelines and data engineering solutions. - Architect and implement end-to-end data platforms (batch and real-time processing). - Build and optimize ETL/ELT workflows using up-to-date data engineering tools. - Design cloud-native data solutions on AWS / Azure / GCP. - Implement data governance, data quality, and data security standards. - Collaborate with Data Scientists, Analysts, and Business stakeholders. - Manage streaming data pipelines using Kafka / real-time ingestion tools. - Monitor, troubleshoot, and optimize data systems for performance and scalability. - Lead and mentor a team of data engineers. Exp (Years) - 10 to 18 Years Required Skills - Strong experience in Python, SQL, and distributed data systems. - Expertise in Apache Spark, Hadoop, Kafka, Airflow, Databricks. - Knowledge of DevOps tools (Docker, Kubernetes, CI/CD). - Familiarity with BI tools (Power BI / Tableau). Education - B.E / B.Tech / M.Tech / MCA / M.Sc (Computer Science / IT / Data Science / Statistics) (ref:hirist.tech)