Aws Sagemaker
Virtusa
Date: 1 day ago
City: Chennai, Tamil Nadu
Contract type: Full time
WorkMode : work from office
Work Location : Chennai / Hyderabad / Bangalore
Work Timing : 2 PM to 11 PM
Primary : Aws Sagemaker
Years of Experience: 6-9 years
Job Summary: We are seeking a Data Engineer with 6–9 years of experience to join our offshore teams. In this role, you will be responsible for building and managing data pipelines that enable advanced analytics and machine learning initiatives. You will collaborate with business and technical teams to ensure data is accessible, reliable, and optimized for AI/ML workloads, helping the organization unlock actionable insights and drive innovation through data-driven decision-making.
Responsibilities
Work Location : Chennai / Hyderabad / Bangalore
Work Timing : 2 PM to 11 PM
Primary : Aws Sagemaker
Years of Experience: 6-9 years
Job Summary: We are seeking a Data Engineer with 6–9 years of experience to join our offshore teams. In this role, you will be responsible for building and managing data pipelines that enable advanced analytics and machine learning initiatives. You will collaborate with business and technical teams to ensure data is accessible, reliable, and optimized for AI/ML workloads, helping the organization unlock actionable insights and drive innovation through data-driven decision-making.
Responsibilities
- Design, develop, and maintain scalable data pipelines to support analytics and machine learning projects.
- Collaborate with stakeholders to understand data requirements and deliver solutions that meet business needs.
- Ensure data quality, consistency, and availability across multiple environments.
- Monitor and optimize workflows to maintain high performance and reliability.
- Support governance and compliance initiatives by implementing standards for data management and security.
- Participate in planning and execution of data integration, migration, and transformation projects.
- Document processes and workflows to enable reproducibility and knowledge sharing.
- Provide production support for data systems, ensuring minimal downtime and quick resolution of issues.
- Proficiency in building data pipelines using tools such as Apache Spark, Kafka, or similar.
- Experience with AWS SageMaker for machine learning workflows.
- Strong understanding of data governance and security practices.
- Excellent problem-solving and troubleshooting skills.
- Experience with cloud platforms (AWS, Azure, GCP).
- Familiarity with SQL and NoSQL databases.
- Knowledge of data visualization tools.
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