Pune Division, Maharashtra, India
AWS Cloud Data Engineer with 12+ years of experience designing and implementing scalable big data solutions. Skilled in Apache Spark, PySpark, AWS services, and data pipeline optimization. Known for leading cross-functional teams, mentoring junior engineers, and delivering solutions that improve performance . Always exploring innovative cloud architectures and automation techniques. Experience in telecom, banking and retail domain.
Lead design and implementation of AWS-based data engineering solutions supporting large-scale telecommunications analytics platforms. Collaborate with architects, software engineers, and business stakeholders to define scalable cloud-native data architectures. Design, develop, and maintain ETL/ELT pipelines using PySpark, Spark, AWS Glue, S3, Athena, and Redshift. Build scalable distributed data processing frameworks handling multi-terabyte datasets. Develop reusable ingestion, transformation, validation, and monitoring frameworks. Drive solution design discussions and create high-level and low-level design documents. Implement CI/CD deployment strategies using Jenkins and Git-based workflows. Optimize Spark workloads reducing execution time by up to 40%. Implement data governance, quality, monitoring, and security frameworks. Lead root-cause analysis and resolution of critical production issues. Mentor engineers and provide technical leadership across development teams. Coordinate Agile sprint planning, release management, and production deployments.
Developed and maintained Hadoop-based data pipelines and ingestion frameworks. Implemented transformation logic for structured and semi-structured datasets.
Built enterprise-scale data processing solutions using Hive and Hadoop. Optimized SQL workloads and ETL processes for improved performance.
Developed backend systems using Java and MVC architecture. Built scalable APIs and integrated enterprise databases.