Sharnam Kansal

Data Analyst

Delhi, India 1+ yrs exp 83 · Excellent

About

Data Analyst with 1.5+ years turning large, multi-source datasets into decision-ready dashboards and reports. Skilled in Power BI (DAX, Tabular Editor, RLS), SQL, and Excel, with hands-on experience in data analysis, KPI/reporting frameworks, data validation, and stakeholder-facing communication. Microsoft Certified in Fabric Analytics Engineering and Fabric Data Engineering. Cut reporting defects by 50% and improved data reliability through rigorous validation and dimensional modeling.

Skills & Expertise (46)

Power BI Intermediate

7.5/10

1.5

Years Exp

DAX Intermediate

7.0/10

1.5

Years Exp

Power Query Intermediate

7.0/10

1.5

Years Exp

Data Validation Intermediate

7.0/10

1.5

Years Exp

SQL Intermediate

7.0/10

1.5

Years Exp

Python Intermediate

6.5/10

1.5

Years Exp

Azure DevOps Intermediate

6.5/10

1.5

Years Exp

Azure Data Factory Intermediate

6.0/10

1.5

Years Exp

Agile Intermediate

6.0/10

1.5

Years Exp

Warehouse Filtering Jira Git Tabular Editor Microsoft Fabric Lakehouse Pipelines Notebooks MySql Azure SQL Databricks ADLS Gen2 Synapse Delta Lake Medallion Architecture SQL Server SSMS Ad-hoc Analysis Report Design Interactive Dashboards T-SQL Query Optimization Joins Window Functions Row-Level Security Reconciliation Pivot Tables Scrum Dimensional Modeling Star Schema SCD Type 2 Trend Analysis Variance Analysis Semantic Modeling PySpark Data Quality Checks

Work Experience

Software Engineer

MAQ Software

Dec 2024 - May 2026

Built interactive Power BI dashboards with dynamic filtering and drill-throughs for business stakeholders, cutting reporting defects by 50% through automated KPI validation frameworks and pre-release checks. Authored optimized DAX measures and star-schema semantic models with SCD Type 2 history tracking and Row-Level Security (RLS) to ensure accurate, access-controlled reporting. Used Excel throughout the reporting lifecycle to reconcile transformed data against source systems and expected outputs, catching discrepancies before they reached dashboards. Worked directly with business stakeholders to translate reporting requirements into dashboard design and validated KPI definitions. Partnered on the underlying ETL/ELT pipelines in Microsoft Fabric to improve upstream data reliability, reducing refresh latency by 40% and cutting 15+ hrs/week of manual effort via CI/CD automation on Azure DevOps.