Assistant Manager, Data Engineering

As an experienced Data Engineer, you will be leading a small team of data engineers to leverage AWS native technologies such as Lambda and Glue in building a data Lakehouse environment. Your role will involve the following responsibilities: - Lead and mentor a team of data engineers to foster a collaborative and innovative environment. - Design, develop, and maintain scalable data pipelines using AWS native technologies like AWS Glue and Lambda. - Implement best practices for data management including data quality, data governance, and data security. - Ensure high standards by reviewing architecture, design, and code. - Collaborate with cross-functional teams to deliver and operate large scale distributed services in the cloud. - Optimize data workflows for performance and cost-efficiency. - Own system architecture, scalability, reliability, and performance. - Stay updated with the latest advancements in AWS technologies and data engineering practices. Qualifications required for this role include: - BE/B Tech/MSc/MCA with specialization in Computer Science/Information Systems. - 5+ years of non-internship professional software development experience. - Experience with AWS components to build and expand lake house in AWS. - Experience building Python programs across Glue ETL jobs and Lambda functions. - Design & Build S3 buckets, tiers, lifecycle policies, as a strategic storage layer for Data Lake. - Experience building applications based on data in both Relational databases (e.g., MySQL), NoSQL databases (e.g., DynamoDB, MongoDB), and filesystems (e.g., S3, HDFS). - Require 3+ hands-on experience on AWS S3, Spark, Glue ETL & Catalog, Lambda Functions, Athena & Kafka. - 2-3 years of experience in writing SQL Queries. - Certified on one of - Solution Architect, Data Engineer, or Data Analytics Specialty by AWS. No additional details of the company were mentioned in the job description.,