Data Engineer/Lead - Big Data Ecosystem

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 initiatives.

Responsibilities :

• 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 modern data engineering tools.

• Develop robust data models for analytics, reporting, and machine learning use cases.

• Work with big data frameworks like Hadoop, Spark, and distributed computing systems.

• 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.

• Ensure documentation and adherence to best engineering practices.

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.

• Experience with Machine Learning data pipelines.

• 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)