Sr. AWS Data Engineer
Skills
PythonSalesforce.ComSharepointAWS S3Apache AirflowETLSQL
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 15+ years of experience in data engineering or related roles
- Advanced Python proficiency including classes inheritance multithreading and functional programming
- Experience building reusable Python packages and automating ETL processes
- Strong SQL skills with complex joins CTEs subqueries and query optimization
- Hands-on experience with Airflow DAGs pipeline orchestration and job scheduling
- Experience tracking rerunning and troubleshooting data pipeline jobs
- Ability to import and export data in CSV JSON XML and similar formats
- Proficiency in Python unit integration and system testing
- Experience implementing DBT tests for validation and quality checks
- Experience using GitHub and building CI/CD processes
- In-depth knowledge of AWS S3 ECS IAM and cloud security best practices
- Experience with AWS Lambda is a plus
- Experience integrating Airflow with AWS services and DBT models is a plus
- Experience with API integrations to Salesforce SFTP SharePoint and OneDrive is a plus
- Familiarity with CloudWatch and DataDog monitoring is a plus
Nice to have
- Great communicator
- Client facing
- Attention to detail
- Team player
- Individual contributor
- Hands-on
Day to day
- Design and build robust AWS-based data pipelines with strong hands-on Python development and orchestration capabilities.
- Develop reusable code, automate ETL workflows, and troubleshoot pipeline failures with careful attention to data quality and recovery.
- Work closely with clients and teams in a highly collaborative, detail-oriented environment while supporting integrations across cloud and enterprise systems.