About this role
Our client is seeking a skilled Data Engineer with solid hands-on experience in PySpark, AWS Glue, and ETL development. This role involves building and maintaining scalable, production-grade data pipelines on AWS. You will be part of a delivery-focused team tackling complex data engineering challenges and contributing to data lake architecture.
Key Responsibilities:
- Design, develop, and implement ETL processes using PySpark and AWS Glue.
- Build and maintain scalable data pipelines to ensure efficient data flow.
- Collaborate with cross-functional teams to understand data requirements and deliver solutions.
- Monitor and optimize data pipelines for performance and reliability.
- Troubleshoot and resolve data-related issues as they arise.
Required Skills & Qualifications:
- Proficiency in PySpark and AWS Glue.
- Strong experience in ETL development and data pipeline architecture.
- Familiarity with AWS services such as S3, Redshift, and Lambda.
- Knowledge of data modeling and data warehousing concepts.
- Excellent problem-solving skills and attention to detail.
Experience:
- 4-8 years of relevant experience in data engineering or a related field.
What we offer:
- Opportunity to work in a dynamic and innovative environment.
- Flexible working arrangements with a remote option.
- Collaborative team culture focused on professional growth.
This role is managed by AI-First Talent on behalf of our client. Your application is reviewed directly by our talent team.