Job description

We have an urgent requirement of 1 AWS Data Engg with Data Scientist skills , for our customer. See required details below: · Indent ID: SF_OP_211336-2 > · Detailed JD: A hands-on AWS Data Engineer with Data Science skills designs, builds, and maintains scalable cloud data pipelines while operationalizing machine learning models and data science workloads. Job Description Overview · Role: Hands-On AWS Data Engineer with Data Science Skills · Core Mission: Bridge the gap between raw data infrastructure and production-ready machine learning by building reliable data lakes, feature stores, and automated ML pipelines on AWS. Key Responsibilities · Data Pipeline & Lakehouse Engineering: Design, build, and optimize end-to-end batch and streaming data pipelines using Amazon S3, AWS Glue, Amazon EMR, and Kinesis. · Data Science & ML Integration: Operationalize and deploy machine learning models (scikit-learn, PyTorch, or TensorFlow) into production workflows using SageMaker and Lambda. · Feature Engineering & Warehousing: Manage large-scale data storage and analytics using Amazon Redshift and Athena, creating clean feature sets for data science models. · Orchestration & Automation: Build robust workflow orchestration using Apache Airflow, MWAA (Managed Workflows for Apache Airflow), or AWS Step Functions. · Data Governance & Quality: Ensure data integrity, pipeline monitoring, and security compliance using IAM, Lake Formation, and CloudWatch Required Qualifications & Skills · Cloud & Services: 7+ years of hands-on experience with core AWS big data services (S3, Glue, Redshift, Athena, EMR, SageMaker). · Programming: Advanced proficiency in Python and SQL ; experience with PySpark or Scala for big data processing. · Data Science Acumen: Solid understanding of machine learning lifecycles, feature store concepts, and model deployment/inference patterns. · DevOps & Tools: Experience with Docker, Git, CI/CD pipelines, and Infrastructure as Code (Terraform or AWS CDK) · Sell Rate : $74-76/hr. · Client Full Address: 500 Kendall Street, Cambridge, MA 02142 · Remote / WFO / Hybrid: Remote (preferably from Cambridge, MA) · Hire Type (FTE/Contract): Contract · Project Duration: 8 Months · Expected Start Date: 26 Oct 26 · No. of client interviews for this role: 1 to 2

Requirements

Must-haves

We have an urgent requirement of 1 AWS Data Engg with Data Scientist skills , for our customer. See required details below:
· Indent ID: SF_OP_211336-2 >
A hands-on AWS Data Engineer with Data Science skills designs, builds, and maintains scalable cloud data pipelines while operationalizing machine learning models and data science workloads.
Job Description Overview
· Role: Hands-On AWS Data Engineer with Data Science Skills
· Core Mission: Bridge the gap between raw data infrastructure and production-ready machine learning by building reliable data lakes, feature stores, and automated ML pipelines on AWS.
· Data Pipeline & Lakehouse Engineering: Design, build, and optimize end-to-end batch and streaming data pipelines using Amazon S3, AWS Glue, Amazon EMR, and Kinesis.
· Data Science & ML Integration: Operationalize and deploy machine learning models (scikit-learn, PyTorch, or TensorFlow) into production workflows using SageMaker and Lambda.
· Feature Engineering & Warehousing: Manage large-scale data storage and analytics using Amazon Redshift and Athena, creating clean feature sets for data science models.
· Orchestration & Automation: Build robust workflow orchestration using Apache Airflow, MWAA (Managed Workflows for Apache Airflow), or AWS Step Functions.
· Data Governance & Quality: Ensure data integrity, pipeline monitoring, and security compliance using IAM, Lake Formation, and CloudWatch
Required Qualifications & Skills
· Cloud & Services: 7+ years of hands-on experience with core AWS big data services (S3, Glue, Redshift, Athena, EMR, SageMaker).
· Programming: Advanced proficiency in Python and SQL ; experience with PySpark or Scala for big data processing.
· Data Science Acumen: Solid understanding of machine learning lifecycles, feature store concepts, and model deployment/inference patterns.
· DevOps & Tools: Experience with Docker, Git, CI/CD pipelines, and Infrastructure as Code (Terraform or AWS CDK)
· Sell Rate : $74-76/hr.
· Client Full Address: 500 Kendall Street, Cambridge, MA 02142
· Remote / WFO / Hybrid: Remote (preferably from Cambridge, MA)
· Hire Type (FTE/Contract): Contract
· Project Duration: 8 Months
· Expected Start Date: 26 Oct 26
· No. of client interviews for this role: 1 to 2

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Keywords to mirror

awsmachine learningmlpythonsqldockerci/cd

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Effort: medium