Big Data Lead

We’re looking for a data engineer to build and maintain ELT pipelines using Apache Airflow, dbt, and Snowflake in an AWS cloud environment.Should have experience in modular python coding with experience in deploying any container based services in aws with monitoring setup as well Key Skills & Experience: Strong SQL and Snowflake expertise, including performance tuning and data modeling. Proficient in Python for scripting, automation, and working with REST APIs. Experience with Apache Airflow for orchestration and workflow monitoring. Hands-on with dbt for modular, version-controlled data transformations. Solid experience with AWS services (e.g., S3, Lambda, IAM, CloudWatch) in data engineering workflows. Experience integrating and processing data from REST APIs. Understanding of data quality, governance, and cloud-native troubleshooting. ------------------------------ Primary Skills: Must have below: 10+ Years Experience Great Communicator/Client Facing Individual Contributor 100% Hands on in the mentioned skills DBT Proficiency: model development: Experience in creating complex DBT models including incremental models, snapshots and documentation. Ability to write and maintain DBT macros for reusable code Testing and documentation: Proficiency in implementing DBT tests for data validation and quality checks Familiarity with generating and maintaining documentation using DBT's built in features Version control: Experience in managing DBT projects using git ,including implementing CI/CD process from the scratch AWS Expertise: Data STORAGE solutions: In depth understanding of AWS S3 for data storage, including best practices for organization and security Experience with AWS redshift for data warehousing and performance optimization Data Integration: Familiarity with Aws glue for ETL processes and orchestration -Nice to have Experience with AWS lambda for serverless data processing tasks Workflow Orchestration: