Lead Data Engineer

Chennai - India

Monthly Salary: Not Disclosed

Experience Required: 12-15years

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

About the Role

We are seeking a highly skilled and experienced Senior / Lead Data Engineer to design develop and maintain scalable reliable and efficient data pipelines and ETL solutions. The role requires strong expertise across multi-cloud environments modern data warehousing platforms programming languages and data orchestration tools. You will play a pivotal role in transforming raw data into actionable insights ensuring data quality and enabling analytics and reporting initiatives across the organization.

Responsibilities

Design build and optimize complex ETL/ELT data pipelines using Python PySpark Scala and advanced SQL.
Implement and manage ETL processes using Informatics PowerCenter Data bricks AWS Glue and Snowflake.
Develop and deploy scalable data solutions across AWS Azure GCP and Microsoft Fabric using cloud-native services.
Manage and optimize databases including Redshift SQL Server and AWS RDS.
Orchestrate and monitor data workflows with Apache Airflow to ensure reliable and timely delivery.
Implement streaming solutions with Apache Kafka and containerized services with Kubernetes.
Automate data workflows and system monitoring using Unix shell scripting.
Apply CI/CD practices to data pipelines and enforce Data Clean room principles for privacy-compliant collaboration.
Collaborate with BI/reporting teams to deliver optimized datasets for Tableau Looker and PowerBI.
Troubleshoot and resolve performance issues in pipelines and database queries.
Maintain detailed technical documentation and collaborate closely with cross-functional teams.

Requirements

Bachelor s or Master s degree in Computer Science Engineering Information Technology or related field.
10 years of experience as Data Engineer.
Languages: Proficiency in SQL Python (including PySpark) Scala and Unix Shell Scripting.
ETL Tools: Hands-on experience with Informatics PowerCenter Data bricks and AWS Glue.
Data Warehousing: Expertise in Snowflake and Redshift.
Cloud Platforms: Strong exposure to at least two of AWS Azure GCP; familiarity with Microsoft Fabric.
Databases: Solid knowledge of Redshift SQL Server and AWS RDS.
Orchestration: Proven experience with Apache Airflow.
Streaming & Containerization: Practical experience with Apache Kafka and Kubernetes.
Concepts: Working knowledge of CI/CD pipelines and Data Clean room practices.
Reporting Tools: Understanding of data provisioning for Tableau Looker or PowerBI.
Strong problem-solving skills communication ability and a proactive approach to emerging technologies.

Snowflakes, DBT, SQL , Apache Airflow, AWS RDS, Data Warehousing, RDBMS, Tableau ,Power BI

Education

Bachelor s degree

About the Role We are seeking a highly skilled and experienced Senior / Lead Data Engineer to design develop and maintain scalable reliable and efficient data pipelines and ETL solutions. The role requires strong expertise across multi-cloud environments modern data warehousing platforms programming...

About the Role

Responsibilities

Design build and optimize complex ETL/ELT data pipelines using Python PySpark Scala and advanced SQL.
Implement and manage ETL processes using Informatics PowerCenter Data bricks AWS Glue and Snowflake.
Develop and deploy scalable data solutions across AWS Azure GCP and Microsoft Fabric using cloud-native services.
Manage and optimize databases including Redshift SQL Server and AWS RDS.
Orchestrate and monitor data workflows with Apache Airflow to ensure reliable and timely delivery.
Implement streaming solutions with Apache Kafka and containerized services with Kubernetes.
Automate data workflows and system monitoring using Unix shell scripting.
Apply CI/CD practices to data pipelines and enforce Data Clean room principles for privacy-compliant collaboration.
Collaborate with BI/reporting teams to deliver optimized datasets for Tableau Looker and PowerBI.
Troubleshoot and resolve performance issues in pipelines and database queries.
Maintain detailed technical documentation and collaborate closely with cross-functional teams.

Requirements

Bachelor s or Master s degree in Computer Science Engineering Information Technology or related field.
10 years of experience as Data Engineer.
Languages: Proficiency in SQL Python (including PySpark) Scala and Unix Shell Scripting.
ETL Tools: Hands-on experience with Informatics PowerCenter Data bricks and AWS Glue.
Data Warehousing: Expertise in Snowflake and Redshift.
Cloud Platforms: Strong exposure to at least two of AWS Azure GCP; familiarity with Microsoft Fabric.
Databases: Solid knowledge of Redshift SQL Server and AWS RDS.
Orchestration: Proven experience with Apache Airflow.
Streaming & Containerization: Practical experience with Apache Kafka and Kubernetes.
Concepts: Working knowledge of CI/CD pipelines and Data Clean room practices.
Reporting Tools: Understanding of data provisioning for Tableau Looker or PowerBI.
Strong problem-solving skills communication ability and a proactive approach to emerging technologies.