Seeking an AWS Data Engineer to design, build, and maintain scalable data pipelines and ETL solutions using Python/Pyspark and AWS.
Key Responsibilities
- Build and maintain ETL pipelines using Python and PySpark on AWS Glue and other compute platforms Orchestrate workflows with AWS Step Functions and serverless components (Lambda)
- Implement messaging and event-driven patterns using AWS SNS and SQS
- Design and optimize data storage and querying in Amazon Redshift
- Write performant SQL for data transformations, validation, and reporting
- Ensure data quality, monitoring, error handling and operational support for pipelines
- Collaborate with data consumers, engineers, and stakeholders to translate requirements into solutions Contribute to CI/CD, infrastructure-as-code, and documentation for reproducible deployment.
Required Skills
- Strong experience with Python and Pyspark for large-scale data processing
- Proven hands-on experience with AWS services: Lambda, SNS, SQS, Glue, Redshift, Step Functions Solid SQLSQL skills and familiarity with data modeling and query optimization Experience with ETL best practices, data quality checks, and monitoring/alerting Familiarity with version control (Git) and basic DevOps/CI-CD workflows
Pay: $60.00 - $65.00 per hour
Expected hours: 40 per week
Benefits:
- 401(k)
- Dental insurance
- Flexible schedule
- Health insurance
- Vision insurance
Work Location: In person
