Key Responsibilities:

Data Engineering

- Design and build production-grade data pipelines using Azure Data Factory and Azure Databricks.
- Develop scalable data architectures leveraging Azure SQL, Data Lake, and modern data modelling techniques (star/snowflake schemas).
- Implement data quality validation, reconciliation processes, and resolve operational issues.

Analytics & AI Enablement

- Use Python for data processing, transformation, and analytics.
- Develop and maintain Jupyter Notebooks for exploration and experimentation.
- Utilize MLflow for experiment tracking and model lifecycle management.

BI Enablement

- Deliver curated, analytics-ready datasets for Power BI and other reporting platforms.
- Optimize data models and structures for effective reporting, dashboarding, and analytics consumption.

Engineering Practices

- Implement CI/CD pipelines for data engineering workflows.
- Ensure secure data handling practices,



including sensitive data protection.
- Monitor, troubleshoot, and resolve pipeline failures and performance issues.

Required Skills & Qualifications

Strong expertise in:

- Azure Data Factory
- Azure Databricks
- Azure SQL and Data Lake
- Solid understanding of data modelling (star and snowflake schemas).
- Experience building scalable and reliable data pipelines.

- Core Competencies

- Strong problem-solving and analytical skills.
- Ability to manage production-grade data environments.
- Focus on data quality, scalability, and performance optimization.

- Nice to Have

- Experience working in regulated data environments.
- Exposure to Azure OpenAI or AI/ML use cases.
- Knowledge of prompt engineering, evaluation frameworks, and experimentation techniques.

📌 Azure Data Engineer (Bengaluru)
🏢 EY
📍 Bengaluru