Ai Engineer

Role: Data & Platform Engineering ( Azure, Python)

Duration: 2 Months

Work Timings: French Timings

Years of Experience: 5+ years

Key Responsibilities

• Design and develop scalable data and analytics solutions using Microsoft Fabric and Azure
  
  

services

• Build and maintain data pipelines using Python, Fabric Data Engineering, Lakehouse,
  
  

Notebooks, and Pipelines

• Integrate analytical and ML outputs into downstream analytics platforms and dashboards
• Implement data transformations, validation checks, and performance optimisations
  
  

Predictive Modeling & Analytics

• Design, build, and iterate on predictive and analytical models using Python
• Develop models and scoring logic that support real-world decision-making, with an emphasis
  
  

on interpretability and stability

• Produce explainable outputs, including scores, categories, and key drivers influencing model
  
  

results

• Perform diagnostics and validation to understand model behaviour across different data
  
  

segment.

Decision Support & Scenario Analysis

• Translate business rules, constraints, and policies into quantitative logic that can be applied
  
  

consistently

• Build what-if and scenario analyses to evaluate trade-offs and outcomes under changing
  
  

assumptions

• Clearly communicate model behaviour, limitations, and trade-offs to non-technical
  
  

stakeholders

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Collaboration & Governance

• Work closely with business stakeholders to understand decision processes and analytical
  
  

needs

• Collaborate with platform and architecture teams to productionize solutions responsibly
• Contribute to technical design discussions and ensure adherence to security, governance, and
  
  

compliance standards

• Troubleshoot production issues and continuously improve solution reliability and clarity
  
  

Required Skills

• Solid experience with Microsoft Azure, including services such as Azure Data Factory /
  
  

Synapse / Azure Functions, Azure Data Lake Storage (ADLS), Azure SQL (Cosmos DB is

a plus)

• Hands-on experience with Microsoft Fabric, including Data Engineering, Lakehouses,
  
  

Notebooks, and Pipelines

• Understanding of data modeling, ETL/ELT patterns, and analytics workloads
• Strong proficiency in Python, including data processing, feature engineering, and ML
  
  

workflows

• Experience building predictive or analytical models using libraries such as scikit-learn,
  
  

pandas, NumPy

• Experience with Git, CI/CD pipelines, and DevOps practices
• Ability to explain analytical concepts and results clearly to non-technical stakeholders
  
  

Good to Have

• Experience with model interpretability or explainability techniques
• Exposure to scenario analysis, simulation, or decision-support systems
• Experience with Azure Machine Learning or ML deployment
• Knowledge of Power BI and semantic models in Fabric
  
  

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• Understanding of data quality, bias, or fairness considerations
• Familiarity with MLOps concepts