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Okay, so you've selected the Job Description for the AWS Cloud Data Engineer role. Here's that Job Description again, confirming it's the one you've chosen: AMK Group Job Title: Cloud Data Engineer (AWS Focus) Location: Hyderabad, Telangana, India Job Description AMK Group is seeking a skilled and passionate Cloud Data Engineer with a strong focus on AWS technologies to join our dynamic team. You will be instrumental in building and maintaining our data lake, designing robust data models, and integrating diverse data sources into a cohesive and performant platform within the AWS ecosystem. This is a rewarding career opportunity to work with cutting-edge cloud data technologies. Key Responsibilities Design, implement, and maintain scalable and reliable data infrastructure on the AWS cloud platform . Develop and maintain robust data pipelines for efficient data processing and analysis using AWS services. Build and maintain a data lake on AWS, ensuring data quality, accessibility, and governance. Integrate various heterogeneous data sources into a cohesive data platform. Work extensively with AWS cloud technologies such as EC2, S3, Redshift, Glue, Athena, Lambda, Kinesis, and EMR. Develop and optimize data solutions using Python for scripting, automation, and data manipulation. Work with both SQL and NoSQL databases , such as MySQL, Postgres, MongoDB, and Cassandra. Utilize ETL tools like Apache NiFi, Talend, and AWS Glue for data extraction, transformation, and loading. Collaborate with data scientists, analysts, and other engineering teams to understand data requirements and deliver effective solutions. Required Skills & Experience Proven experience in AWS cloud data engineering or a related field. Strong proficiency in Python for data engineering. Experience with AWS cloud technologies , including EC2, S3, Redshift, Glue, Athena, Lambda, Kinesis, and EMR. Experience with SQL and NoSQL databases , such as MySQL, Postgres, MongoDB, and Cassandra. Experience with ETL tools , such as Apache NiFi, Talend, and AWS Glue. Experience in building and maintaining data lakes. Experience in designing data models. Demonstrated ability to integrate various data sources into a cohesive platform.
