Azure Data Engineer
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Job Location:
Monthly Salary:
Posted on:
15 hours ago
Vacancies:
1 Vacancy
Job Summary
KEY EXPECTED ACHIEVEMENTS
Following Lean & Agile methods quality and security (SecByD) rules and state of the art of DevOps practices under the supervision of senior and lead engineer:
Software creating business value is developed and maintained:
The beautiful* and clean** code is written. Testings and debugging are completed. The softwares are maintained and improved. Technical support by diagnosing and solving simple incidents is insured. Easy technical questions are answered. Minor changes to existing applications are implemented. The associated documentation is carried out.
Functional and/or Technical specifications are adapted to cover the right level of business needs:
A great User Interface (UI)/ User eXperience (UX) is provided by working closely with the business partners or UX/UI experts. Functional and/or Technical specifications are adapted accordingly.
Controls and tests are executed:
Unit tests and unit plans are built executed optimized ensuring quality security and consistency. Malfunctions incidents and bugsare detected understood analyzed reported and solved.
The solution is deployed and operated:
He/she is a contributor to change management communication and training.
He/she builds an automated deployment.
He/she supports the solution (especially in product mode)
* Beautiful code is showable useful generic sustainable (ease of maintenance scalable reusable) shareable elegant (code as essay bookish minimal) pleasurable efficient concise readable.
** Clean code uses writing standards (names (search) functions (short) ...) code patterns (architecture/design at all scale) and practices (testing & refactoring) and uses code discipline (SOLID DRY YAGNI TDD ...).
Activity
Be part of a IS/IT squad under the responsibility of a Team Leader.
Requested to work on Data projects as a Developer Engineer.
To build and support solution in Corporate Datalake using Azure technologies (Databricks with Python PySpark Azure Datafactory) and follow delivery till Production deployment assume L3 support (ability to support User Acceptance tests good level of communication expected).
3-5 years experience on Data Engineering skills.
Required Experience:
IC
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
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