Cloud Data Engineer

You are seeking a Data Engineer with expertise in AWS cloud services, particularly in Infrastructure Security, IAM, and Disaster Management. Your role will involve the following responsibilities and qualifications: Role Overview: You should possess over 10 years of experience in Data Engineering and at least 5 years of hands-on experience with AWS data services. Proficiency in Python and/or Scala is essential. Your responsibilities will include building ETL/ELT pipelines at scale, demonstrating strong SQL and data modeling expertise, and hands-on experience with Spark/PySpark, Airflow or similar orchestration tools, and REST APIs and microservices. It is expected that you have experience using GitHub Copilot or similar AI-assisted development tools in enterprise environments. A solid understanding of IAM, encryption, networking, and cloud security best practices is crucial. Key Responsibilities: - Build ETL/ELT pipelines at scale - Demonstrate strong SQL and data modeling expertise - Hands-on experience with Spark/PySpark, Airflow, REST APIs, and microservices - Utilize GitHub Copilot or similar AI-assisted development tools - Ensure IAM, encryption, networking, and cloud security best practices are followed Qualifications Required: - Over 10 years of experience in Data Engineering - At least 5 years of hands-on experience with AWS data services - Proficiency in Python and/or Scala - Experience with Spark/PySpark, Airflow, REST APIs, and microservices - Strong SQL and data modeling expertise Additionally, the following qualifications are preferred: - AWS Certifications (e.g., AWS Certified Solutions Architect, AWS Certified Data Analytics) - Experience with streaming technologies (Kafka, Kinesis) - Experience with containerization (Docker, Kubernetes) - Knowledge of Delta Lake, Iceberg, or Hudi - Experience implementing data observability solutions You should also possess leadership and soft skills, including the ability to lead engineering teams, drive architectural decisions, communicate effectively with stakeholders, balance delivery velocity with engineering excellence, and work in Agile/Scrum environments. Nice to have qualifications include experience in implementing cost governance and FinOps best practices on AWS, exposure to AI/ML pipeline integration, and experience in designing multi-account AWS architectures. You are seeking a Data Engineer with expertise in AWS cloud services, particularly in Infrastructure Security, IAM, and Disaster Management. Your role will involve the following responsibilities and qualifications: Role Overview: You should possess over 10 years of experience in Data Engineering and at least 5 years of hands-on experience with AWS data services. Proficiency in Python and/or Scala is essential. Your responsibilities will include building ETL/ELT pipelines at scale, demonstrating strong SQL and data modeling expertise, and hands-on experience with Spark/PySpark, Airflow or similar orchestration tools, and REST APIs and microservices. It is expected that you have experience using GitHub Copilot or similar AI-assisted development tools in enterprise environments. A solid understanding of IAM, encryption, networking, and cloud security best practices is crucial. Key Responsibilities: - Build ETL/ELT pipelines at scale - Demonstrate strong SQL and data modeling expertise - Hands-on experience with Spark/PySpark, Airflow, REST APIs, and microservices - Utilize GitHub Copilot or similar AI-assisted development tools - Ensure IAM, encryption, networking, and cloud security best practices are followed Qualifications Required: - Over 10 years of experience in Data Engineering - At least 5 years of hands-on experience with AWS data services - Proficiency in Python and/or Scala - Experience with Spark/PySpark, Airflow, REST APIs, and microservices - Strong SQL and data modeling expertise Additionally, the following qualifications are preferred: - AWS Certifications (e.g., AWS Certified Solutions Architect, AWS Certified Data Analytics) - Experience with streaming technologies (Kafka, Kinesis) - Experience with containerization (Docker, Kubernetes) - Knowledge of Delta Lake, Iceberg, or Hudi - Experience implementing data observability solutions You should also possess leadership and soft skills, including the ability to lead engineering teams, drive architectural decisions, communicate effectively with stakeholders, balance delivery velocity with engineering excellence, and work in Agile/Scrum environments. Nice to have qualifications include experience in implementing cost governance and FinOps best practices on AWS, exposure to AI/ML pipeline integration, and experience in designing multi-account AWS architectures.