Looking for Only W2 Candidate (EADs, GC and USC) 10 Years of overall experience is required. Job Title: Full Stack Developer-1344016 Job Responsibilities: Design and implement scalable cloud solutions and data architectures within the AWS and Google Cloud ecosystems. Develop and maintain CI/CD pipelines to automate deployment processes and ensure continuous integration. Lead teams in designing and developing centralized data warehouses and data lakes, preferably using Redshift. Create and optimize ETL processes to ingest and transform large datasets for analytical purposes. Utilize Apache Airflow for scheduling and monitoring data workflows to ensure timely data delivery. Implement data partitioning, compression strategies, and query optimization techniques. Develop serverless applications using AWS Lambda and API Gateway to reduce operational costs. Automate configuration management using tools like Ansible and Terraform. Conduct security assessments and implement IAM and VPC best practices to secure cloud environments. Integrate monitoring and logging solutions using CloudWatch, Prometheus, and ELK Stack for performance and security monitoring. Create automated reporting solutions and interactive dashboards using Tableau, Looker, and Power BI. Conduct data quality checks and ensure data integrity across multiple data pipelines. Securely ingest data from public and other client sources to derive better insights. Requirements: Strong experience in Java and Python, with some exposure to Golang. Working knowledge of data and analytics platforms, including technologies like Glue and PySpark. Ability to understand the workings of functions that contribute to a performant data platform. Hands-on experience in writing Python and Java functions and supporting existing Golang functions. 10 years of overall experience in software development . Experience with data-centric roles, including data pipelines, Redshift, and data connectors. Proficiency in AWS services, including EC2, S3, RDS, Lambda, CloudFormation, VPC, IAM, and Redshift. Familiarity with data engineering concepts such as ETL, data warehousing, and data modeling. Experience with big data technologies like Hadoop, Spark, and Athena. Knowledge of DevOps tools such as Docker, Kubernetes, Jenkins, and Git. Experience with data visualization tools like Tableau, Looker, and Power BI. Strong understanding of security practices, including Forerock, Keycloak, and SSO solutions for data platforms.