AWS Data Engineer

qode.world

full-time

Posted on: 8/29/2025

Location: Ohio • 🇺🇸 United States

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Mid-LevelSenior

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.

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.