Data Engineer with AI Python AWS Skills
Overview
Design and build scalable data pipelines using Python and AI to support large-scale analytics. Lead ownership of data infrastructure across multiple cloud environments. This role focuses on creating efficient data solutions that drive business insights.
What You'll Do11
- 1Develop and maintain ETL pipelines leveraging Python Spark Airflow to process massive datasets
- 2Architect cloud-native data warehouses on AWS utilizing services like S3 Redshift and Glue
- 3Implement machine learning models integrating AI techniques for predictive analytics
- 4Optimize data workflows through automation and orchestration frameworks
- 5Scale data platforms to handle petabyte-level volumes while ensuring reliability
- 6Collaborate with cross-functional teams to define data requirements and solution designs
- 7Drive continuous improvement of data quality and governance practices
- 8Debug complex data pipeline issues and resolve performance bottlenecks
- 9Ship production-grade data products that meet strict SLAs and user expectations
- 10Identify opportunities to apply AI/ML innovations to enhance data processing efficiency
- 11Mentor junior engineers and share best practices for cloud architecture design
Requirements5
- 15+ years building ETL pipelines with Spark and Airflow
- 23-5 seasons leading data engineering projects in enterprise environments
- 3AWS Certified professional with hands-on experience deploying cloud solutions
- 4Python developer proficient in scripting data transformations and workflows
- 5AI expertise applying machine learning to solve data challenges
Salary Insight
Salary not disclosed in listing
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