qode.world

AWS Data Engineer

qode.world

full-time

Posted on:

Origin:  • 🇺🇸 United States • Ohio

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Job Level

Mid-LevelSenior

Tech Stack

AirflowAmazon RedshiftAWSCloudDistributed SystemsDockerETLKubernetesPySparkPythonSQL

About the role

  • AWS Data Engineer building cloud data pipelines for analytics.
  • The job entails designing, building, and maintaining large-scale data pipelines and cloud-based data platforms using AWS services.
  • 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.

Requirements

  • 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.