Senior Data Engineer

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At our client, data is considered as a major asset for the business to achieve its targets (strategic ambitions, innovation or transformation themes, objectives and regulatory compliance).

With their Data Platform consisting out of :

• Cutting-edge Integration Toolset,
• Business Intelligence , Analytics and storage capabilities,
• A platform for the Management of Master Data,
• A Data Governance platform that encompasses Data Lineage and Data Quality.

With their Data Organization consisting out of :

• Business Product Teams (supporting the business stakeholder initiatives, organized according the Agile principles)
• Backbone/Platform Teams (supporting the data platform initiatives, organized according the Agile principles)
• Transversal competencies Team (supporting the various profiles and technologies initiatives, organized according the Agile principles (Spotify))

They work in quite flat hierarchy, with the team mates widespread in agile teams, and according to the principles of open source.

Description:
We are looking for a Data Engineer, who will primarily join one of our product Teams. It is an opportunity to mark with your signature our corporate Data organization, and contribute indirectly to better product to manage our Customer, as more qualitative data or service around data for our customer.
We are looking for Data Engineers able to create data pipelines, efficient storage structures, powerful materialized views in different analytical technologies, but also data exchange endpoints at destination of our users. To some extent, you’ll also have to interact with aspect related to governance tools (Glossary, Modeling, Lineage, or Data Quality…).

Requirements

What will be your mission and for which competences will you need an Extensive hands-on experience (> 3 to 5 years preferable) in 2 out of the 4 following categories:

• Implementing solutions with on-premise data technologies stack from Microsoft (SSIS, SSAS, and SQL Server)
• Implementing data pipelines using Azure services such as Azure Databricks, but also to some extent Azure Data Factory, Azure Functions, Azure Stream/log Analytics, and Azure DevOps
• Implementing data pipelines or data enrichments with Python in a Databricks environment
• Open to learn and jump on new technologies (on the ones listed above, or also Redis, RabbitMQ, Neo4j, or Apache Arrow, …)
• Able and willing to interact with business analysts and stakeholders to refine some requirements and to present reusable and integrated solution
• Able and willing to contribute to extensive testing of the solution, as the reinforcement of devops principles within the team.
• Able and willing to contribute to the writing and structuration of documentation

What you will NOT be doing

• You shall not act from an Ivory Technical Tower.
• You don’t not make decisions for the Business but rather advise them with careful logic or showing your reasoning.
• You shall not deliver technical solution, rather product features.
• What we’re expecting from you in your product team

Participate to the refinement of user stories, share your point of view (challenge proposition and propose alternatives) with the product team. Define technical design (or architecture), collaborate with teammates, ask for reviews and advises and write down the initial version. Openly discuss any evolution of the design/architecture. Implement the feature/user story in parallel of implementation of the unit tests. Implement corresponding monitoring, metadata. Participate to the definition of end-to-end test scenarios. Peer review code written by teammates and ask for peer review of your own code. Accept feedback from peers. Participate to end-users’ documentation, demos and roadshows. Be engaged in any retrospective and continuous improvement activities. Actively give feedback to your teammates about their contributions What we’re expecting from you in the Data Chapter
Review some architectures or designs proposed by other teams and share your experience and knowledge. Write down decisions taken in a format promoting reusability. Contribute to design and architectural blueprints combining previous decisions. Participate to learning sessions by presenting on a topic or as an attendee.