Role: Data Analytics + AI Engineer,

Experience: 5-7 years total and relevant.

Location: Bangalore

2 rounds interview (1st Round in office F2F )

Mandatory Skills:

For Data Analytics Role:

1. Microsoft Fabric
2. AI
3. SQL and PostgreSQL - Strong experience Must Have
4. Data Analytics
5. PowerBI

Artificial Intelligence & Advanced Analytics

- Solid hands-on experience in AI, Machine Learning, and Data Science
- Experience developing predictive and prescriptive analytics solutions
- Knowledge of Generative AI, LLMs, Copilot technologies, and RAG frameworks
- Statistical analysis, forecasting, and model evaluation
- Expertise in Python-based ML frameworks (Scikit-Learn, TensorFlow, PyTorch)

Data Engineering & ETL

- Expertise in designing and developing ETL/ELT pipelines
- Strong SQL and PostgreSQL development experience
- Data cleansing, transformation, and enrichment techniques
- Experience handling large-scale structured and unstructured data
- Strong understanding of Big Data processing frameworks

Microsoft Fabric & Cloud Analytics

- Hands-on experience with Microsoft Fabric
- Lakehouse and Data Warehouse design
- Fabric Data Factory, Notebooks, Semantic Models, and Deployment Pipelines
- Experience with Data Lakes and enterprise cloud analytics platforms





Business Intelligence & Data Visualization

- Expert-level Power BI development
- Advanced DAX and Power Query (M Language)
- Data modeling and semantic model optimization
- Executive dashboard design and storytelling
- Performance tuning and optimization of enterprise-scale reports

Programming & Automation

- Expert-level Python programming
- Automation using Python, APIs, and scripting
- Experience building reusable analytics frameworks

Database & Infrastructure

- Strong understanding of database architecture
- Experience with SQL Server, PostgreSQL, and enterprise database platforms
- Query optimization and performance tuning
- Hands-on experience supporting database and infrastructure migrations
- Understanding of servers, storage, networking, and enterprise data environments

Data Governance & Quality

- Data Governance frameworks and controls
- Data Quality Management
- Data Validation methodologies
- Metadata Management and Data Lineage
- Master Data Management
- Compliance and audit readiness

DevOps & Production Operations Added Advantage

- Azure DevOps / Git source control
- CI/CD implementation
- Release management and deployment automation
- Monitoring and production support

📌 Data analytics (Bengaluru)
🏢 Shell Infotech
📍 Bengaluru