Data Engineer (AWS)

As a Data Engineer at Muoro.io, your role involves designing, building, and optimizing scalable data pipelines and platforms within the AWS data ecosystem. You will be responsible for: - Designing, developing, and maintaining robust data pipelines and ETL workflows using AWS tools such as Glue, Kinesis, Redshift, S3, and Data Lake architectures. - Working extensively with SQL and Databricks to process, transform, and analyze large datasets. - Implementing data orchestration and workflow automation using tools like Airflow or Step Functions. - Ensuring data quality, integrity, and consistency across systems through rigorous validation and monitoring practices. - Collaborating with cross-functional teams, including data analysts and software engineers, to support data-driven decision-making. - Optimizing data storage, retrieval, and processing for scalability and performance in a cloud-native environment. Qualifications required for this role include: - 5+ years of hands-on experience in data engineering. - Proven expertise in the AWS ecosystem (Glue, Kinesis, Redshift, S3). - Proficiency in SQL, Databricks, and data pipeline orchestration tools. - Strong understanding of data analysis, data quality management, and data modeling principles. - Experience working with data lakes and modern data architectures. - Excellent problem-solving, communication, and collaboration skills. As a Data Engineer at Muoro.io, your role involves designing, building, and optimizing scalable data pipelines and platforms within the AWS data ecosystem. You will be responsible for: - Designing, developing, and maintaining robust data pipelines and ETL workflows using AWS tools such as Glue, Kinesis, Redshift, S3, and Data Lake architectures. - Working extensively with SQL and Databricks to process, transform, and analyze large datasets. - Implementing data orchestration and workflow automation using tools like Airflow or Step Functions. - Ensuring data quality, integrity, and consistency across systems through rigorous validation and monitoring practices. - Collaborating with cross-functional teams, including data analysts and software engineers, to support data-driven decision-making. - Optimizing data storage, retrieval, and processing for scalability and performance in a cloud-native environment. Qualifications required for this role include: - 5+ years of hands-on experience in data engineering. - Proven expertise in the AWS ecosystem (Glue, Kinesis, Redshift, S3). - Proficiency in SQL, Databricks, and data pipeline orchestration tools. - Strong understanding of data analysis, data quality management, and data modeling principles. - Experience working with data lakes and modern data architectures. - Excellent problem-solving, communication, and collaboration skills.