Data Engineer

As a Data Engineer, you'll play a crucial role in managing the entire lifecycle of data pipelines and integrating data visualization solutions.

Data Pipeline Creation:

• Collaborate with Product Owners and business representatives to define new data pipelines technically.

• Evaluate the complexity associated with each ambition and the required skills.

• Work closely with subject matter experts to determine the necessary scope of data for fueling the pipelines.

• Design and co-build the architecture for ingesting data, considering data cleansing and preparation based on its origin.

• Implement the data transformation layer, leveraging analytics or AI features.

• Establish connections with external services to expose output data.

Data Visualization:

• Utilize Power BI capabilities to share various datasets with internal teams and external customers.

• Develop dashboards for automating the monitoring of AI features and adoption.

• Create customer reports that showcase data transformation results, following guidance from our business representatives and Connected Services Hubs remote support agents.

• Actively contribute to integrating Power BI into the program for creating a new reporting experience.

• Collaborate with UX designers to structure reporting concepts (events, evidence, recommendations).

• Identify all detailed data models.

• Build a semantic database to anticipate future needs, including Generative AI Co-Pilot integration.

• Deploy and maintain report templates.

DevOps / MLOps role:

• Masters model deployment and upgrade in the appropriate environment (Databricks, Dataiku, others...)

• Knowledgeable around the correct implementation of those environment in Azure (or similar environment like AWS or GCP)

• Act as a single point of contact for the analytics team with external technical DevOps organization (Advisor Engineerings, AI Hub)

Qualifications

• Python Programming (5/5): Strong programming skills are essential for data manipulation, transformation, and pipeline development.

• ETL Extract Transfer Load (5/5): Significative experience is required

• Data Preparation and Modeling (5/5): Understanding various kind of data structures will be valuable in the role.

• Sql / Non Sql DB Management (4.5/5): Proficiency in Database Management systems

• MLOps (4/5): Understanding ML concepts for integrating ML models into pipelines.

• DevOps (Azure) (4/5): Familiarity with Azure cloud services for scalable data storage and processing.

• Databricks (3/5): Proficiency with Databricks environment will be valuable

• Dataiku (1.5/5) : an experience with Dataiku platform could be a plus

• Power BI usage (5/5): Ability to create insightful visualizations in Power BI is mandatory

Schedule: Full-time
Req: 0090H5