Required skills
Job description
This contract role focuses on building and tuning scalable data-processing solutions and pipelines in AWS environments. PySpark is explicitly mandatory, alongside advanced SQL skills for query optimization and performance tuning; the description also names S3, EMR, MSK (Kafka), SageMaker, Athena, Lambda, and DataSync. PostgreSQL, AI, and automation appear in
Project overview
This contract role focuses on building and tuning scalable data-processing solutions and pipelines in AWS environments. PySpark is explicitly mandatory, alongside advanced SQL skills for query optimization and performance tuning; the description also names S3, EMR, MSK (Kafka), SageMaker, Athena, Lambda, and DataSync. PostgreSQL, AI, and automation appear in the structured skills/title but are not explained as requirements in the role description, so they are treated as unclear rather than confirmed must-haves. The stated experience band is 8–10 years, and the location is India.
Work mode and the specific product or industry context are not specified.
Responsibilities
- Advanced proficiency in SQL, including query optimization and performance tuning.
- Experience in designing, developing, and optimizing scalable data pipelines and data processing solutions in AWS environments.
- Ability to troubleshoot and tune data workloads for performance, reliability, and scalability.
Requirements
- Hands-on PySpark for large-scale data processing and transformation
- Advanced SQL, including query optimization and performance tuning
- Hands-on AWS experience, including S3, EMR, MSK (Kafka), SageMaker, Athena, Lambda, and DataSync
- Designing, developing, and optimizing scalable data pipelines and processing solutions in AWS
- Troubleshooting and tuning data workloads for performance, reliability, and scalability
Project details
- Start: flexible
- Remote: onsite
- Location: India, IN
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