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Meet our client
Our Client is CONFIDENTIAL
About the role
A forward-thinking organization is seeking a Senior Data Engineer with deep AWS and machine learning infrastructure expertise. This is a hands-on contract role focused on building scalable ML pipelines and production-grade systems that deliver real-time insights and advanced analytics across various business domains.
Key Responsibilities
- Design and implement scalable, secure, and automated data pipelines on AWS using services like Glue, Lambda, Step Functions, S3, Redshift, etc.
- Operationalize machine learning models in production environments, leveraging SageMaker or custom deployment frameworks.
- Build and automate ETL / ELT workflows for both structured and unstructured data.
- Apply MLOps best practices to support rapid iteration and deployment of ML models.
- Collaborate with cross-functional teams, including data scientists, architects, and business stakeholders.
Mandatory Requirements
5+ years of professional data engineering experience, with at least 2 years in a senior-level role.Deep hands-on experience with AWS cloud services, including Glue, Lambda, Redshift, S3, SageMaker.Strong skills in Python and SQL; PySpark experience is a bonus.Knowledge of containerization (Docker), orchestration tools (Airflow, StepFunctions), and infrastructure-as-code (Terraform, AWS CDK).Experience deploying and managing machine learning models at scale.Real-time data streaming using Kafka or Kinesis.Familiarity with data governance and cloud security best practices.Previous work in regulated industries such as finance or healthcare.Strong analytical and problem-solving mindset.Excellent communication and team collaboration abilities.Capable of working independently in a remote setting while aligning deliverables with business goals.J-18808-Ljbffr