Big Data Engineer With AWS

As a Mid-level Big Data Engineer with a strong focus on AWS, your role will involve designing, developing, and maintaining scalable data processing pipelines using Spark/PySpark and Hadoop on AWS. You will be responsible for implementing and optimizing data workflows on AWS EMR, EC2, and ECS, as well as developing and integrating RESTful APIs and AWS Gateway services using Scala/Java. Collaboration with cross-functional teams to understand data requirements and ensure data quality, performance, and reliability will be crucial. Additionally, you will participate in code reviews, testing, and deployment processes. Key Responsibilities: - Design, develop, and maintain scalable data processing pipelines using Spark/PySpark and Hadoop on AWS. - Implement and optimize data workflows on AWS EMR, EC2, and ECS. - Develop and integrate RESTful APIs and AWS Gateway services using Scala/Java. - Collaborate with cross-functional teams to understand data requirements and deliver robust solutions. - Ensure data quality, performance, and reliability across all systems. - Participate in code reviews, testing, and deployment processes. Required Skills & Qualifications: - 3-5 years of experience in Big Data Engineering. - Strong hands-on experience with Spark/PySpark, Hadoop, and AWS services. - Proficiency in Scala or Java for backend and API development. - Experience with AWS EMR, EC2, ECS, and API Gateway. - Solid understanding of RESTful API design and integration. - Familiarity with CI/CD pipelines and version control (e.g., Git). - Excellent problem-solving and communication skills. Preferred Qualifications: - Experience in data security and compliance within cloud environments. - Exposure to data lake architectures and real-time data processing. - Knowledge of containerization tools like Docker and orchestration with Kubernetes.,