Data Analyst - Information and technology

We are looking for a highly skilled Data Analyst with 4+ years of experience in business intelligence, data integration, and advanced analytics. The ideal candidate will have strong hands-on expertise in Microsoft Fabric, Data Science, and Microsoft Power BI. The role focuses on building scalable analytics solutions, transforming complex data into high-quality datasets, and enabling data-driven decision-making across the organization.

Key Responsibilities

• Develop and deploy machine learning, statistical, and predictive analytical models using Python and open-source frameworks to solve complex business problems.
• Design solutions for processing unstructured data including documents, images, PDFs, and emails using OCR and Intelligent Document Processing technologies.
• Build centralized data repositories, Lakehouses, and analytical datasets to support advanced analytics, AI, and enterprise reporting requirements.
• Apply statistical techniques such as sample size determination (N), regression modelling, classification, forecasting, and hypothesis testing to generate actionable business insights.
• Design, build, and manage analytics solutions using Microsoft Fabric components including OneLake, Lakehouse, Warehouses, and Data Pipelines.
• Develop and optimize semantic models and analytical datasets and follow best practices.
• Implement data ingestion, transformation, and orchestration using Fabric Dataflows Gen2 and pipelines.
• Write and optimize SQL for analytics workloads in Fabric Warehouses and Lakehouses.
• Implement data modeling techniques (star schema, snowflake schema) to support scalable analytics solutions.
• Hands-on experience with Microsoft Copilot and other AI copilots for productivity and analytics.
• Experience with data agents for query execution, workflow management, and intelligent data retrieval.
• Ability to design and implement agent-based architectures for scalable analytics solutions.
• Ensure data quality, validation, and governance across enterprise datasets.
• Monitor and optimize data performance, cost, and query efficiency in Microsoft Fabric.
• Collaborate with business and technical stakeholders to translate requirements into analytics-ready datasets.
• Document data models, transformations, lineage, and business definitions.
• Support ad-hoc analysis and present insights in a clear, business-friendly manner.

Technical Skills

• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn).

• Solid understanding of data science fundamentals and applied statistics.

• Microsoft DP-600 Certified or equivalent like Data Engineering with Spark, dbt & Airflow (Coursera) , Databricks Certified Data Engineer Professional

• Strong hands-on experience with Microsoft Fabric:

• OneLake

• Lakehouse & Warehouses

• Dataflows Gen2

• Data Pipelines

• Expertise in SQL analytics and query optimization within Fabric.

• Experience creating and managing semantic data models.

• Knowledge of data warehousing concepts, analytical patterns, and performance tuning.

• Familiarity with data governance, security, and access control in Fabric environments.

Experience working in enterprise-scale analytics platforms is a plus.

Experience & Qualifications

• Bachelors degree in Engineering, Computer Science / Information Technology , MCA , BCA or related field
• Prior experience with machine learning, statistical, and predictive analytical models and generate data insight.
• Experience and hands on processing unstructured data including documents, images, PDFs, and emails using OCR and Intelligent Document Processing technologies
• DP600 Certification is an advantage and good to have.
• Prior experience with large-scale data platforms or cloud analytics solutions.
• Experience working in cross-functional teams and stakeholder-facing roles

Analytical & Soft Skills

• Strong analytical and problem-solving mindset.
• Ability to work with complex datasets and derive actionable insights.
• Excellent communication skills to explain technical concepts to non-technical stakeholders.
• Strong documentation and data storytelling abilities.
• Ability to work independently and collaboratively in cross-functional teams.