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Aws Data Engineer

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Onsite

Aws Data Engineer

Valuemomentum

Aws Data Engineer

Skills

Data EngineeringPythonAWS LambdaSnowflakeAmazon RedshiftData AnalysisAWSPySpark

2 months ago

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Important information


Contract type:

Permanent

Location:

Coimbatore, Tamil Nadu, India

Work mode:

Onsite

Published on:

18 August 2026

What they need


AWS Data Engineer

Company: ValueMomentum
Job Locations: Hyderabad | Pune | Coimbatore
Experience: 4-12 Years
Work Mode: Work From Office

About the Role
ValueMomentum is looking for experienced AWS Data Engineers to design, develop, and
maintain scalable cloud-native data engineering solutions on AWS.
You will build high-performance ETL/ELT pipelines and modern data platforms supporting enterprise analytics, reporting, and business intelligence initiatives. You will work closely with architects, business stakeholders, and cross-functional teams to deliver secure, scalable, and reliable data solutions for global insurance clients.

Key Skills
AWS Data Engineering: AWS Glue, Amazon S3, Amazon Redshift, AWS Lambda
Data Engineering: ETL/ELT, Scalable Data Pipelines, Data Warehousing
Programming: PySpark, Python
Cloud/Data Platform: Snowflake

Key Responsibilities

  • Design, develop, and maintain scalable AWS data pipelines.
  • Build ETL/ELT solutions using AWS Glue, S3, Redshift, and Lambda.
  • Develop data processing and transformation solutions using PySpark/Python.
  • Work with Snowflake for data warehousing and analytics.
  • Ensure data quality, reliability, security, and performance.
  • Optimize data pipelines and troubleshoot production issues.
  • Collaborate with architects, business stakeholders, and cross-functional teams.
  • Contribute to modern cloud-native data platforms and enterprise analytics solutions.

Required Skills

  • 4-12 years of hands-on Data Engineering experience.
  • Strong expertise in AWS Glue, S3, Redshift, and Lambda.
  • Strong programming skills in Python/PySpark.
  • Hands-on experience with Snowflake.
  • Strong understanding of ETL/ELT and data pipeline development.
  • Good understanding of data warehousing and cloud-native data architectures.
  • Strong analytical, problem-solving, and communication skills.

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