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About the Role – AWS Cloud Data Engineer We are hiring a skilled AWS Data Engineer to help develop and optimize cloud-native data pipelines using Python, AWS Glue, Redshift, and Kafka . This hybrid role in Dallas, TX offers the chance to work on mission-critical ETL workflows and data transformation solutions across large datasets. Key Responsibilities – Python-Based ETL & AWS Data Engineering Build and automate ETL pipelines using Python for cloud data lakes and warehouses Integrate with AWS services like S3, Glue, EMR, Redshift, Athena, Kinesis, and SageMaker Design and execute automated testing frameworks for data validation and integrity Create dashboards and reports to support data visualization and insights Collaborate with analysts, product managers, and developers to deliver accurate data solutions Perform data migration from on-premises to AWS environments Execute DevOps and DataOps practices for pipeline optimization Troubleshoot data pipeline issues, investigate anomalies, and resolve performance bottlenecks Required Skills – Python, AWS Glue, Redshift, and Kafka Proficiency in Python programming for data automation Hands-on experience with AWS services : S3, Glue, Redshift, EMR, Athena, SageMaker Experience with streaming tools like Kafka and structured data pipelines Strong command of SQL, Unix/Linux scripting , and CI/CD tools Knowledge of ETL technologies such as Informatica, Ab Initio, Alteryx, or AWS Glue Experience with cloud data lake and on-prem to cloud migration strategies Familiarity with testing and validating ETL workflows Preferred Experience – Data Science and DevOps in Cloud Exposure to machine learning platforms like SageMaker, H2O, or ML Studio Knowledge of Jenkins, GitLab , and CI/CD practices Familiarity with Agile and Waterfall methodologies Experience with test case management and defect tracking tools Hands-on testing experience with S3, HDFS , and similar storage tools Soft Skills – Collaboration and Ownership Strong communication and ability to explain technical concepts clearly Self-motivated and proactive with strong ownership mindset Ability to guide junior developers or testers during data operations Problem-solving and debugging skills across complex data environments Flexible and adaptive in hybrid work setups Ready to Apply? If you are passionate about building high-impact data engineering solutions using Python and AWS, this is your chance to grow with a cloud-first team. Check out other positions Let’s discuss your next career move 15 FAQs About This AWS Data Engineer Role 1. What is the primary focus of this AWS Data Engineer position? To build, test, and manage automated cloud-based ETL pipelines using Python and AWS services. 2. Is this a remote position? It’s a hybrid role requiring partial onsite presence in Dallas, TX. 3. How much experience is required? Candidates with 6–10 years of data engineering and cloud infrastructure experience are preferred. 4. What tools are commonly used in this role? Python, AWS Glue, Redshift, EMR, Kafka, Jenkins, GitLab, SQL, and Unix scripting. 5. Is experience in data science mandatory? Not mandatory, but familiarity with platforms like SageMaker or H2O is a bonus. 6. Will I work on real-time data or batch pipelines? Both – the role involves streaming platforms like Kafka and batch processing using AWS tools. 7. Is prior DevOps experience necessary? DevOps and DataOps exposure is highly preferred to support CI/CD for data pipelines. 8. Will I work directly with business stakeholders? Yes, you’ll collaborate closely with analysts, developers, and product teams. 9. Is on-prem to cloud migration experience needed? Yes, data migration experience is a plus. 10. Will I need to design dashboards or just backend pipelines? You’ll support report creation and help design dashboards for data visualization. 11. What kind of scripting is expected? Unix/Linux shell scripting and Python automation for testing and deployment. 12. What’s the interview process like? Initial screening, followed by a technical interview and data engineering assessment. 13. Do I need experience with specific testing tools? Experience with test case management and defect tracking tools is preferred. 14. What are typical KPIs or success metrics in this role? Uptime, accuracy, data freshness, test coverage, and pipeline performance. 15. Can I expect growth opportunities? Yes, you’ll be working on cutting-edge cloud solutions with potential for leadership. #J-18808-Ljbffr