Description

Key Skills: AWS Cloud, AI/ML, Redshift

Roles and Responsibilities:

• Design and develop scalable AWS data pipelines for AI/ML workloads.
• Build ETL/ELT pipelines using AWS Glue, S3, and PySpark.
• Develop and optimize data solutions using Amazon Redshift and Athena.
• Prepare, transform, and validate large datasets for AI/ML models.
• Integrate structured and unstructured data from multiple sources.
• Support Machine Learning and Generative AI use cases with high-quality data.
• Work with Amazon SageMaker for ML data preparation and model-related workflows.
• Work with Amazon Bedrock and LLM-based applications where required.
• Implement data ingestion, transformation, data quality, and governance processes.
• Optimize data pipelines for performance, scalability, reliability, and cost.
• Collaborate with Data Scientists, ML Engineers, Data Architects, and business teams.
• Troubleshoot data pipeline and production issues and provide root-cause analysis.

Skills Required:

• Strong analytical and problem-solving skills.
• Experience working with large-scale cloud data platforms and AI/ML projects.

Mandatory Skills

• AWS
• S3
• AWS Glue
• Redshift / Athena
• PySpark / Spark
• Python
• SQL
• ETL / ELT
• Data Lake / Data Warehouse
• Machine Learning / AI data engineering
• Experience supporting AI/ML workloads

Good to Have

• Amazon SageMaker
• Amazon Bedrock
• Generative AI / LLM
• Vector databases
• RAG pipelines
• AWS Lambda
• Kinesis
• EMR
• Kafka
• Airflow
• Terraform
• CI/CD
• Data governance and quality

Education:Bachelor's degree in Computer Science, IT, Engineering, or a related field

Key Skills

Education

Any Graduate