Data analytics

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

• 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