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.

Key Responsibilities :

- Design, develop, and maintain scalable data architectures and robust pipelines for large-scale data platforms.

- Build and optimize data lakes to unify both structured and unstructured data sources, ensuring accessibility and performance.

- Implement real-time and batch data processing using advanced Snowflake features like Streams, Tasks, and Snowpipe.

- Utilize a wide range of AWS services including EC2, Glue, Lambda, S3, Athena, and MWAA for efficient data integration, processing, and analytics.

- Develop and manage PySpark and Python-based workflows for scalable transformations and automation.

- Perform complex data modeling, performance tuning, and optimization within the Snowflake environment.

- Collaborate with cross-functional teams to deliver end-to-end data engineering solutions aligned with critical business goals.

Required Skills & Qualifications :

- 915 years of professional experience in data engineering or a related field.

- Strong expertise in AWS and Snowflake.

- Proven proficiency in AWS Glue.

- Hands-on experience with PySpark for data processing.

- Experience in designing and delivering scalable data engineering solutions.