Data Engineer

Requirements:
5+ years of experience in data engineering in fast-paced environments.
Cloud experience with any major provider - AWS, GCP or Azure - Big Advantage.
Proper software engineering skill in Python, with a systematic understanding of OOP.
Must write clean, reusable, efficient, and scalable code, while applying design patterns and adhering to SOLID principles for maintainability and performance.
Proven hands-on experience with pub-sub architectures, microservices architectures, event-driven data processing, and distributed computing.
Proven experience in CI/CD processes- testing, deployment automation, and version control, with experience in Serverless Framework, Bitbucket (or GitLab\GitHub) pipelines, or similar tools (no, copying files over SSH doesnt count).
Fundamental understanding of essentials like sharding, partitioning, streaming and batch processing, graph and DAG, lake and warehouse, what map/reducer etc.
Knowledge with ML operations. Experience with SageMaker- an advantage.
Team Player and owning a positive "Go-To" attitude.