Data Analyst - Information and technology (Ahmedabad)

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. - Solid documentation and data storytelling abilities. - Ability to work independently and collaboratively in cross-functional teams. .