
MethodHub - AWS Data Engineer - PySpark/SQL
3 weeks ago
Title : AWS Data Engineer
Experience :8 yrs to 15 yrs
Location : Remote
Notice Period : Immediate
This role is highly hands-on and requires experience building robust data pipelines and data assets on AWS.
- 4+ years of strong programming experience in Python / PySpark.
- Should be able to write clean, production-grade code.
- Look for mentions of Spark SQL optimizations and large-scale data processing.
- Python (Strong Programming) and Boto3
- Candidates should have experience using Python to write code that interacts directly with AWS services through Boto3 (the AWS SDK for Python)
- Candidates who have automated tasks like uploading data to S3, triggering Lambda functions, or managing AWS resources programmatically using Python code not just using AWS consoles.
AWS services experience must be able to discuss practical use of :
- S3 (storage), EC2 (compute), Lambda (serverless functions), Redshift (data warehouse), CloudFormation (infrastructure as code), Spark( EMR, Glue, or Databricks).
- Candidate should be able to explain why/when to use each, not just list them.
Code versioning and repository tools :
- Familiarity with Git (branching, merging, pull requests).
- Knowledge of JFrog Artifactory or similar artifact repositories.
Code quality practices :
- Experience refactoring legacy code
- Comfortable writing unit tests, ideally using test-driven development (TDD) methods.
- Can debug difficult bugs (performance, concurrency, logic errors) in large codebases.
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