Lead AWS Data Engineer

leads the design, development, and maintenance of data integration solutions using Python, AWS Data Services, DBT ensuring data pipeline & data quality Collaborate with business stakeholders and architects to define the enterprise data strategy, data models, and migration Roadmap Translate complex technical constraints into business insights and manage expectations across cross-functional teams Develop, modify, configure & debug existing data pipeline as per the business requirement. Troubleshoot and resolve technical issues. Debug, tune and optimize code for optimal performance Manage the new requirements, Review the existing jobs, Perform gap analysis & Fixing performance issues, etc. Guide, coach, and upskill junior and mid-level data engineers on best practices, coding standards, and modern data patterns Document all data flow & mappings, sessions and workflows Ticket handling and problem ticket analysis skills in Agile /POD approach

Must Have Technical/Functional Skills 12+ years of solid hands-on experience in Python, AWS Data Services, DBT, Apache Airflow (on Astronomer platform), SQL and PySpark Very Good hands-on knowledge on SQL and Data Warehousing life cycle is an absolute requirement. Experience in creating data pipelines and orchestrating using DBT & Apache Airflow Significant experience with data migrations and development of Operational Data Stores, Enterprise Data Warehouses, Data Lake and Data Marts. Experiencing in fixing performance issues / parallelism, Data model exposure is a must. Good to have: Experience with cloud ETL and ELT in one of the tools like Glue/EMR or any other ELT tool Experience in using Snowflake, DB2, Postgres and other database technologies is plus. Excellent communication skills to liaise with Business & IT stakeholders. Expertise in planning execution of a project and efforts estimation. Exposure to working in Agile ways of working