Job
Description
Role Overview: You will be an experienced Cloud Architect with a minimum of 8 years of experience, specializing in designing and implementing scalable and secure cloud architectures on AWS, Azure, or GCP. Your leadership skills will be crucial in building enterprise-grade data platforms utilizing technologies such as Databricks, Snowflake, Spark, and Data Lake/Warehouse solutions to support advanced analytics and AI/ML integrations. You will also be responsible for researching and developing custom architecture PoCs, including AI/ML model deployment, security enhancements, and scalable data workflows to meet evolving business needs. Key Responsibilities: - Design and deploy data pipelines using AWS (S3, Lambda, Glue, Data Pipeline), Databricks, and Snowflake for real-time streaming, batch processing, and analytics workloads. - Provision cloud infrastructure using Terraform, CloudFormation, and Control Tower to ensure multi-AZ, high availability, and multi-tenant architectures. - Develop hybrid cloud architecture solutions for cloud-to-cloud integrations, cross-cloud data migration, and multi-cloud orchestration involving AWS, GCP, Azure, and on-prem systems. - Implement CI/CD pipelines using CloudFormation, Jenkins, Git, Terraform to support automated deployment of applications and infrastructure. - Create SaaS solutions with secure management provisioning, license management, and custom deployment architectures. - Monitor and optimize performance using Prometheus, Grafana, Elasticsearch, Kibana for fault detection and quick bug resolution. - Design and optimize data pipelines, architect data warehousing solutions using AWS, Snowflake, Databricks, and develop scalable, distributed data processing systems using Apache Spark, Hadoop, or similar frameworks. - Develop and maintain logical and physical data models to support analytics, reporting, and ML use cases. - Collaborate with Data Scientists, Analysts, and Business Teams to provide guidance on data best practices, performance tuning, and data-driven solutions. - Mentor and train junior data engineers and contribute to team growth. Qualifications Required: - Proficient in cloud platforms such as AWS, GCP, and Azure. - Experience with data platforms and tools including Databricks, Snowflake, Hadoop, Spark, Data Lake, Data Warehouse. - Knowledge of DevOps and automation tools like Terraform, CloudFormation, Kubernetes, Docker, CI/CD pipelines. - Familiarity with monitoring and logging tools such as Prometheus, Grafana, ELK Stack. - Strong programming and scripting skills in Python, Java, Bash, SQL. - Understanding of security and compliance standards like SOC2, HIPAA, audit logs, security controls. Role Overview: You will be an experienced Cloud Architect with a minimum of 8 years of experience, specializing in designing and implementing scalable and secure cloud architectures on AWS, Azure, or GCP. Your leadership skills will be crucial in building enterprise-grade data platforms utilizing technologies such as Databricks, Snowflake, Spark, and Data Lake/Warehouse solutions to support advanced analytics and AI/ML integrations. You will also be responsible for researching and developing custom architecture PoCs, including AI/ML model deployment, security enhancements, and scalable data workflows to meet evolving business needs. Key Responsibilities: - Design and deploy data pipelines using AWS (S3, Lambda, Glue, Data Pipeline), Databricks, and Snowflake for real-time streaming, batch processing, and analytics workloads. - Provision cloud infrastructure using Terraform, CloudFormation, and Control Tower to ensure multi-AZ, high availability, and multi-tenant architectures. - Develop hybrid cloud architecture solutions for cloud-to-cloud integrations, cross-cloud data migration, and multi-cloud orchestration involving AWS, GCP, Azure, and on-prem systems. - Implement CI/CD pipelines using CloudFormation, Jenkins, Git, Terraform to support automated deployment of applications and infrastructure. - Create SaaS solutions with secure management provisioning, license management, and custom deployment architectures. - Monitor and optimize performance using Prometheus, Grafana, Elasticsearch, Kibana for fault detection and quick bug resolution. - Design and optimize data pipelines, architect data warehousing solutions using AWS, Snowflake, Databricks, and develop scalable, distributed data processing systems using Apache Spark, Hadoop, or similar frameworks. - Develop and maintain logical and physical data models to support analytics, reporting, and ML use cases. - Collaborate with Data Scientists, Analysts, and Business Teams to provide guidance on data best practices, performance tuning, and data-driven solutions. - Mentor and train junior data engineers and contribute to team growth. Qualifications Required: - Proficient in cloud platforms such as AWS, GCP, and Azure. - Experience with data platforms and tools including Databricks, Snowflake, Hadoop, Spark, D
