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:
- Microsoft Fabric
- AI
- SQL and PostgreSQL - Strong experience Must Have
- Data Analytics
- PowerBI
Artificial Intelligence & Advanced Analytics
- Strong 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