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Open nowFirst seen 40 hours ago

Data Engineer

PradeepIT Consulting Services Pvt Ltd2,005 open roles

Where
Remote
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Remote
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  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: first seen 40 hours ago

The posting

Data Engineer

YoE: 3-4 Years

Key Responsibilities:

  • Design and implement data pipelines and ETL workflows using AWS Glue, migrating from legacy Python scripts on EC2.
  • Work with AWS Organizations to manage and optimize a multi-account strategy with centralized governance and billing.
  • Develop and enforce network and security policies including NACLs, VPCs, and VPN configurations.
  • Implement and manage Infrastructure as Code (IaC) using tools like Terraform or AWS CloudFormation.
  • Design, monitor, and maintain long-running ETL processes (16+ hours), ensuring fault tolerance and recovery.
  • Migrate and integrate data using AWS DMS (Database Migration Service).
  • Ensure proper data encryption and masking of sensitive data, including PII and PCI data, following best practices and compliance standards.
  • Collaborate with security teams to enhance data security and governance frameworks.
  • Integrate with tools like Coalesce for data modeling and transformation workflows.
  • Optimize data storage and retrieval processes for scalability and performance.

Required Skills & Experience:

  • 5+ years of experience in data engineering roles.
  • Strong expertise in AWS services including Glue, DMS, EC2, VPC, IAM, S3, CloudWatch, and KMS.
  • Solid understanding of networking and security in AWS, including NACLs, security groups, and VPNs.
  • Hands-on experience with Python for scripting and data processing.
  • Proven track record of migrating ETL workflows to serverless architectures.
  • Experience with data masking, encryption, and compliance frameworks (e.g., GDPR, PCI-DSS).
  • Familiarity with IaC tools like Terraform or AWS CloudFormation.
  • Working knowledge of Coalesce or similar data orchestration platforms is a plus.
  • Experience managing long-running data jobs and optimizing for cost and performance.
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