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

• 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) (ref:hirist.tech)