Job Description

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Key Responsibilities

  • Design, develop, and deploy scalable AWS-based data solutions aligned with client business objectives
  • Architect and maintain data lakes and data warehouses using AWS services such as S3, Redshift, EMR, Glue, Lambda, and Kinesis
  • Build and optimize ETL / ELT pipelines for batch and real-time data ingestion
  • Develop event-driven and streaming data pipelines to support analytics and AI/ML workloads
  • Collaborate with consultants, data scientists, BI engineers, and client stakeholders
  • Ensure compliance with data governance, security, and privacy standards
  • Implement DevOps and CI/CD best practices for data pipelines and infrastructure
  • Continuously evaluate AWS innovations to improve platform performance and capabilities

Must-Have Skills

  • Strong experience as an AWS Data Engineer delivering enterprise-scale solutions
  • Hands-on expertise with AWS services :
  • S3, Lambda, Kinesis, Redshift, EMR, Glue, SQS
  • Proficiency in Python for data processing and pipeline development
  • Solid experience with distributed data frameworks :
  • Apache Spark
  • Apache Hive
  • Experience building ETL/ELT pipelines for structured and unstructured data
  • Strong understanding of data modeling for analytics and reporting
  • Experience with real-time / streaming data pipelines (Kafka, Kinesis)
  • Familiarity with data governance, security, and compliance best practices

Good-to-Have Skills

  • Experience with Apache Airflow , AWS Step Functions , or similar orchestration tools
  • Hands-on knowledge of CI/CD pipelines and DevOps practices
  • Experience with Infrastructure as Code (IaC) :
  • Terraform
  • AWS CloudFormation
  • Exposure to AI/ML data pipelines and analytics workloads
  • Strong SQL skills for analytics and data validation
  • Experience working in consulting or client-facing environments
  • AWS Certifications (e.g., AWS Certified Data Analytics – Specialty , AWS Solutions Architect )

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