Overview
On Site
Depends on Experience
Full Time
No Travel Required
Unable to Provide Sponsorship
Skills
Amazon Redshift
Data Modeling
PySpark
Python
Job Details
Seeking an AWS Data Engineer to design, build, and maintain scalable data pipelines and ETL solutions using Python/Pyspark and AWS managed services to support analytics and data product needs.
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 deployments
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
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