AWS Pyspark Lead

Location: All locations in India
Experience: 8–12 Years Employment Type: Full-Time Department: Data Engineering / Cloud Data Solutions

Job Summary:

We are looking for a highly skilled and motivated Data Engineer with 8–12 years of hands-on experience to join our growing data engineering team. The ideal candidate will have a strong ground in AWS cloud services, Python programming, and big data technologies like Spark and SQL. You will play a key role in designing, building, and optimizing scalable data pipelines and analytics solutions to support business insights and decision-making.

Key Responsibilities:

• Design, develop, and maintain robust and scalable data pipelines using AWS services such as Glue, Lambda, Kinesis, Step Functions, Athena, and DynamoDB.
• Write efficient and reusable Python scripts for data transformation, automation, and orchestration.
• Work with Spark to process large datasets and optimize data workflows.
• Develop complex SQL queries for data extraction, validation, and reporting purposes.
• Collaborate with data scientists, analysts, and cross-functional teams to understand data requirements and deliver end-to-end solutions.
• Ensure best practices around IAM, S3 data management, and secure data exchange using SNS/SQS.
• Monitor pipeline performance and troubleshoot data issues to ensure high availability and reliability.
• Document technical solutions, data flows, and architectural decisions.

Required Skills & Qualifications:

• 8–12 years of experience in data engineering or related field.
• Strong hands-on expertise with AWS services, particularly:
  • Glue, Lambda, Kinesis, Step Functions, S3, DynamoDB, Athena, IAM, SNS, SQS.
• Proficient in Python for scripting and automation.
• Experience with Apache Spark for big data processing.
• Strong knowledge of SQL and working with relational and non-relational databases.
• Solid understanding of data architecture, data integration, and ETL best practices.
• Ability to work in a fast-paced, collaborative environment and deliver high-quality solutions.

Preferred Qualifications:

• AWS Certification (e.g., AWS Certified Data Analytics or Solutions Architect) is a plus.
• Experience with CI/CD pipelines, infrastructure-as-code (Terraform/CloudFormation), or monitoring tools is an advantage.
• Familiarity with data lake and real-time streaming architecture.

Location: All locations in India
Experience: 8–12 Years Employment Type: Full-Time Department: Data Engineering / Cloud Data Solutions

Job Summary:

We are looking for a highly skilled and motivated Data Engineer with 8–12 years of hands-on experience to join our growing data engineering team. The ideal candidate will have a strong ground in AWS cloud services, Python programming, and big data technologies like Spark and SQL. You will play a key role in designing, building, and optimizing scalable data pipelines and analytics solutions to support business insights and decision-making.

Key Responsibilities:

• Design, develop, and maintain robust and scalable data pipelines using AWS services such as Glue, Lambda, Kinesis, Step Functions, Athena, and DynamoDB.
• Write efficient and reusable Python scripts for data transformation, automation, and orchestration.
• Work with Spark to process large datasets and optimize data workflows.
• Develop complex SQL queries for data extraction, validation, and reporting purposes.
• Collaborate with data scientists, analysts, and cross-functional teams to understand data requirements and deliver end-to-end solutions.
• Ensure best practices around IAM, S3 data management, and secure data exchange using SNS/SQS.
• Monitor pipeline performance and troubleshoot data issues to ensure high availability and reliability.
• Document technical solutions, data flows, and architectural decisions.

Required Skills & Qualifications:

• 8–12 years of experience in data engineering or related field.
• Strong hands-on expertise with AWS services, particularly:
  • Glue, Lambda, Kinesis, Step Functions, S3, DynamoDB, Athena, IAM, SNS, SQS.
• Proficient in Python for scripting and automation.
• Experience with Apache Spark for big data processing.
• Strong knowledge of SQL and working with relational and non-relational databases.
• Solid understanding of data architecture, data integration, and ETL best practices.
• Ability to work in a fast-paced, collaborative environment and deliver high-quality solutions.

Preferred Qualifications:

• AWS Certification (e.g., AWS Certified Data Analytics or Solutions Architect) is a plus.
• Experience with CI/CD pipelines, infrastructure-as-code (Terraform/CloudFormation), or monitoring tools is an advantage.
• Familiarity with data lake and real-time streaming architecture.