<p><p><b>Position : </b> Data Engineering Lead<br/><br/><b>Experience : </b> 915 Years<br/><br/><b>Location : </b> PAN India<br/><br/><b>Job Summary : </b><br/><br/></p><p>We are seeking a highly skilled and experienced Data Engineering Lead with 9 to 15 years of hands-on expertise in AWS and Snowflake.
The ideal candidate will be a solution-oriented professional capable of designing, developing, and delivering scalable data engineering solutions.
This role requires deep knowledge of end-to-end data architectures, layered data processing frameworks, and a strong ability to optimize data pipelines, with a preference for candidates with experience in the telecommunications industry.<br/><br/><b>Key Responsibilities : </b><br/><br/></p><p>- Design, develop, and maintain scalable data architectures and robust pipelines for large-scale data platforms.<br/><br/></p><p>- Build and optimize data lakes to unify both structured and unstructured data sources, ensuring accessibility and performance.<br/><br/></p><p>- Implement real-time and batch data processing using advanced Snowflake features like Streams, Tasks, and Snowpipe.<br/><br/></p><p>- Utilize a wide range of AWS services including EC2, Glue, Lambda, S3, Athena, and MWAA for efficient data integration, processing, and analytics.<br/><br/></p><p>- Develop and manage PySpark and Python-based workflows for scalable transformations and automation.<br/><br/></p><p>- Perform complex data modeling, performance tuning, and optimization within the Snowflake environment.<br/><br/></p><p>- Collaborate with cross-functional teams to deliver end-to-end data engineering solutions aligned with critical business goals.<br/><br/><b>Required Skills & Qualifications : </b><br/><br/></p><p>- 915 years of professional experience in data engineering or a related field.<br/><br/></p><p>- Strong expertise in AWS and Snowflake.<br/><br/></p><p>- Proven proficiency in AWS Glue.<br/><br/></p><p>- Hands-on experience with PySpark for data processing.<br/><br/></p><p>- Experience in designing and delivering scalable data engineering solutions.</p><br/></p> (ref:hirist.tech)