Mani Kandan

Senior Data Analyst | Business Intelligence Consultant

Talent

ChennaiMember since September 2, 2026

Power BIDAXSQLSnowflakeData ModelingData ProfilingMicrosoft AzureAzure Data FactoryRequirement GatheringRoot Cause AnalysisAI-assisted AnalyticsSemantic ModelsNatural Language QueryingSAP

Hire this person

Send a job offer directly to this candidate

Power BIDAXSQLSnowflakeData Modeling

About

Business Intelligence Consultant with 4+ years of experience delivering analytics solutions for a global manufacturing organization. Experienced across the complete BI lifecycle, including business requirement gathering, stakeholder workshops, analytical data modeling, SQL analysis, and Power BI solution development. Partner with Finance, Sales, Pricing, Manufacturing, and Operations teams to translate business requirements into scalable reporting solutions that support decision-making.

Collaborate with cross-functional teams to deliver governed analytics models using Snowflake and Azure. Currently expanding expertise in AI-assisted analytics, semantic models, and natural language querying.

Experience

Senior Data Analyst / Business Analyst at Nihilent Limited (2022 – Present)

Work closely with Finance, Sales, Pricing, Manufacturing, and Operations stakeholders to understand business challenges and translate functional requirements into scalable business intelligence solutions.
Design functional dashboard mockups and reporting wireframes before development, then validate through UAT with business users to confirm requirements and improve adoption.
Develop Power BI dashboards and advanced DAX measures supporting executive reporting, operational reviews, and business performance analysis, presenting outcomes directly to leadership.
Build governed analytical data models in Snowflake by integrating SAP Finance, Sales, and Manufacturing datasets for enterprise reporting.
Write and optimize SQL for data profiling, reconciliation, and root cause analysis across large enterprise datasets.
Align with SAP, SAC, and Data Engineering teams - onshore and offshore - to standardize KPI definitions and improve enterprise-wide reporting consistency.
Implement Azure Data Factory (ADF) pipelines that improved reporting reliability and reduced manual data preparation activities.
Work in an Agile/Scrum setup, prioritizing the reporting backlog and working alongside Product Owners, Architects, Business Analysts, Data Engineers, and Project Managers throughout the project lifecycle.