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5 days ago
This is a challenging role that involves designing and developing data pipelines using various tools and technologies. The ideal candidate will have experience with AWS Glue, PySpark, and Step Functions.
The primary responsibilities of this position include:
- Designing and implementing ETL/ELT processes for ingesting, transforming, and delivering data from multiple sources.
- Managing and optimizing storage solutions with Amazon S3.
- Writing reusable and scalable Python code for data engineering workflows.
- Implementing unit and integration tests using pytest to ensure data quality and pipeline reliability.
- Collaborating with cross-functional teams using Git/GitHub for version control, code reviews, and CI/CD integration.
In addition to these responsibilities, the successful candidate will also be responsible for creating clear technical documentation for pipelines, workflows, and design decisions. This includes troubleshooting and resolving issues related to data pipelines and AWS services.
Requirements for this position include:
- At least 5 years of experience in data engineering, with at least 5 years in the AWS ecosystem.
- Strong coding skills in Python, with experience in PySpark.
- Hands-on experience with AWS Glue, Step Functions, and S3.
- Proficiency in pytest for test automation.
- Solid understanding of Git/GitHub workflows.
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