Jobs → Data & Analytics → AWS Data Engineer with Data Science Skills

About the Role We are looking for a hands-on AWS Data Engineer with Data Science skills to design, build, and maintain scalable cloud data pipelines while operationalizing machine learning models and data science workloads. Key Responsibilities • Design, build, and optimize end-to-end batch and streaming data pipelines using Amazon S3, AWS Glue, Amazon EMR, and Kinesis. • Operationalize and deploy machine learning models (scikit-learn, PyTorch, or TensorFlow) into production workflows using SageMaker and Lambda. • Manage large-scale data storage and analytics using Amazon Redshift and Athena, creating clean feature sets for data science models. • Build robust workflow orchestration using Apache Airflow, MWAA, or AWS Step Functions. • Ensure data integrity, pipeline monitoring, and security compliance using IAM, Lake Formation, and CloudWatch. Requirements • 7+ years of hands-on experience with core AWS big data services (S3, Glue, Redshift, Athena, EMR, SageMaker). • Advanced proficiency in Python and SQL; experience with PySpark or Scala for big data processing. • Solid understanding of machine learning lifecycles, feature store concepts, and model deployment/inference patterns. • Experience with Docker, Git, CI/CD pipelines, and Infrastructure as Code (Terraform or AWS CDK).