Talent.com
AWS Data Engineer

AWS Data Engineer

QodeOhio, OH, US
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Job Summary

We are looking for an experienced AWS Data Engineer with strong expertise in Python and PySpark to design, build, and maintain large-scale data pipelines and cloud-based data platforms. The ideal candidate will have hands-on experience with AWS services , distributed data processing, and implementing scalable solutions for analytics and machine learning use cases.

Key Responsibilities

  • Design, develop, and optimize data pipelines using Python, PySpark, and SQL .
  • Build and manage ETL / ELT workflows for structured and unstructured data.
  • Leverage AWS services (S3, Glue, EMR, Redshift, Lambda, Athena, Kinesis, Step Functions, RDS) for data engineering solutions.
  • Implement data lake / data warehouse architectures and ensure data quality, consistency, and security.
  • Work with large-scale distributed systems for real-time and batch data processing.
  • Collaborate with data scientists, analysts, and business stakeholders to deliver high-quality, reliable data solutions.
  • Develop and enforce data governance, monitoring, and best practices for performance optimization.
  • Deploy and manage CI / CD pipelines for data workflows using AWS tools (CodePipeline, CodeBuild) or GitHub Actions.

Required Skills & Qualifications

  • Strong programming skills in Python and hands-on experience with PySpark .
  • Proficiency in SQL for complex queries, transformations, and performance tuning.
  • Solid experience with AWS cloud ecosystem (S3, Glue, EMR, Redshift, Athena, Lambda, etc.).
  • Experience working with data lakes, data warehouses, and distributed systems .
  • Knowledge of ETL frameworks , workflow orchestration (Airflow, Step Functions, or similar), and automation.
  • Familiarity with Docker, Kubernetes, or containerized deployments .
  • Strong understanding of data modeling, partitioning, and optimization techniques.
  • Excellent problem-solving, debugging, and communication skills.
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