The engineers in Retail Demand Forecasting team build the data pipelines that ensure that the results from our forecast algorithms are accurate; timely and relevant; and the work you can do in the domain will go beyond the usual duties of a backend engineer. Apart from being exposed to cutting edge big data and data engineering technologies; you will work closely with data science and engineering teams applying algorithms to improve the engine behind the services.
- About 7-9 years and at least 6 years relevant experience
- Python; Pyspark; HDFS development and components according to a detailed design document.
- Build efficient; reusable and reliable python code per industry best practices.
- Extensive experience with distributed computing specifically Big Data and Data lake architecture. Technically competent to influence and understand the solution context and approach (legacy; tactical; strategic)
- Follow the best practices of continuous BDD/TDD/Performance/Security/Smoke testing. Ensure unit-test coverage meets quality requirements.
- Develop Integration tests to ensure coding adheres to acceptance criteria and verify end-to-end behaviour of the system.
- Ensure best possible performance; quality and responsiveness of applications.
- Support production systems; resolve incidents and perform root cause analysis
Data Engineering; Python; Pyspark; HDFS; CA7; Oozie; Sqoop etc
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