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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 bugs are 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, ...).
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Job Description for Data Engineer - Databricks/python developer:
1) Atleast 2 year experience in Databricks and Awareness of capabilities in Databricks.
2) Technical background with ETL and SQL/RDBMS experience.
3) Understanding of Spark SQL, data frame and its manipulation.
4) Hands on experience in Spark using PySpark or Scala.
5) Knowledge of Azure Data Lake Storage, Azure Data Factory and other Azure services.
6) Basic Knowledge on Power BI.
7) Aware of Jira, Scrum and Agile process.
8) Good Communication, Debugging and Analytical Skills.