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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer with AWS & Python - **Company:** Job Cloud Inc. - **Location:** McLean, VA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Amazon S3, Cloud Computing Security, Cloud Database, Databases, Continuous Integration, Data as a Services, Data Validation, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Warehousing, Relational Databases, Distributed Computing Environment, Identity and Access Management, Python (Programming Language), Operational Databases, Scrum Methodology, Cloud Services, Standard Sql, Data Streaming, Unstructured Data, Data Logging, Data Processing, Scripting, Data Storage Management, Data Ingestion, Snowflake, Apache Spark, Software Troubleshooting, AWS Lambda, Git, Cloudformation, Data Lakes, Pyspark, Kubernetes, Information Technology, AWS Glue, Cloudwatch, Restful APIs, Terraform, Software Version Control, Data Pipelines, Docker, Amazon Redshift, Databricks - **Published:** August 29, 2026 - **Apply:** https://www.careerjet.com/jobad/us5a8f8fc8c9652cfe54952f24fbc215fb ## About the Role Required Skills / Must Have * 5+ years of experience in Data Engineering or a related field. * Strong hands-on experience with Python for data engineering and automation. * Strong experience with AWS cloud services, particularly: * Amazon S3 * AWS Glue * AWS Lambda * Amazon Redshift * Amazon Athena * Strong knowledge of SQL and relational databases. * Experience developing ETL/ELT data pipelines. * Experience with PySpark/Spark and distributed data processing. * Strong understanding of data warehousing and data lake concepts. * Experience with Git and CI/CD pipelines. * Strong troubleshooting and analytical skills. Preferred / Nice to Have * Experience with AWS EMR, Kinesis, Step Functions, or MWAA/Airflow. * Experience with Terraform or CloudFormation. * Knowledge of Databricks, Snowflake, or Delta Lake. * Experience working with streaming data pipelines. * Knowledge of Docker/Kubernetes. * Experience with REST APIs and third-party data integrations. * Knowledge of AWS IAM, encryption, and cloud security best practices. * Experience with Agile/Scrum methodology. Education * Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. * Equivalent professional experience may be considered. ## Description We are looking for an experienced Data Engineer with strong AWS and Python expertise to design, develop, and maintain scalable data pipelines and cloud-based data solutions. The ideal candidate will have hands-on experience with AWS data services, Python programming, ETL/ELT development, data integration, and modern data engineering practices., * Design, develop, and maintain scalable data pipelines and ETL/ELT workflows using Python and AWS services. * Build and optimize data ingestion and transformation pipelines for structured and unstructured data. * Develop reusable Python scripts and applications for data processing, automation, and integration. * Work with AWS services such as S3, Glue, Lambda, Redshift, EMR, Athena, Kinesis, and CloudWatch. * Implement data processing solutions using PySpark and distributed computing frameworks. * Develop data models and optimize data storage and retrieval processes. * Perform data quality checks, validation, reconciliation, and error handling. * Optimize data pipelines for performance, scalability, reliability, and cost efficiency. * Integrate data from APIs, databases, files, and other enterprise data sources. * Implement monitoring, logging, and alerting for data pipelines. * Collaborate with Data Scientists, Data Analysts, Architects, and business stakeholders. * Follow best practices for CI/CD, version control, testing, security, and documentation. * Troubleshoot production data issues and provide timely resolution. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)