Nandini Doma
Data Analyst • n*****************@gmail.com • 703****581 • linkedin.com/••••• • drivetube.ai/•••••
Professional Summary
Data Analyst with 4 years of experience analyzing business and financial data using SQL, Python, Power BI and Azure platform tools to deliver dashboards, ETL validation and data-quality automation that support business decision-making.
Technical Skills
Programming Languages: Python
Frameworks and Libraries: scikit-learn
Databases: SQL
Cloud and DevOps: Azure SQL,Azure Data Factory,Azure DevOps,AWS
Data and Analytics: Power BI,Microsoft Excel,ETL validation,Data cleaning,Data validation,Data modeling,Statistical analysis,Regression modeling
Tools and Methodologies: Git,Dashboard development,KPI reporting,Agile
Work Experience
Real Soft Technologies
Data Analyst
Sep 2024 – Present
Worked at an IT services provider delivering customer and financial analytics, reporting and data-quality solutions for internal and client stakeholders.
Tech Stack: SQL, Python, Power BI, Azure SQL, Azure Data Factory, Azure DevOps
- Collected, cleaned and validated customer and financial datasets from multiple sources using SQL and Python to produce a consolidated reporting schema for business users.
- Designed and delivered Power BI dashboards and KPI reports for finance and customer teams; implemented interactive drill-throughs and role-based access to support stakeholder needs.
- Authored complex SQL queries and created views/stored procedures in Azure SQL to centralize business logic for reporting and reconciliation.
- Developed Python automation for recurring data validation and quality checks and integrated them into scheduled pipelines to reduce manual validation effort.
- Implemented Azure Data Factory pipelines to orchestrate ingestion and transformation of structured data, improving pipeline reliability and reproducibility.
- Collaborated with stakeholders to translate business requirements into prioritized dashboard features and reporting SLAs, delivering iterative releases aligned to user feedback.
Accenture
Data Analyst
Sep 2022 – Aug 2024
Worked at a global consulting firm delivering data analytics, ETL validation and production reporting for enterprise clients across business functions.
Tech Stack: SQL, Python, Power BI, Git, Azure DevOps
- Developed SQL queries and data models to extract and transform enterprise datasets for reporting and ad-hoc analysis; optimized joins and filters to improve query performance on large tables.
- Built Power BI reports and semantic models with DAX measures to track key business KPIs for executives and operations teams, improving visibility into performance drivers.
- Performed ETL validation and source-to-target reconciliation across data pipelines using SQL-based tests to detect and document data mismatches prior to release.
- Automated data quality checks and validation workflows with Python scripts and integrated them into Azure DevOps pipelines for scheduled execution.
- Collaborated with cross-functional teams and business stakeholders to clarify metrics, refine requirements and resolve data discrepancies across source systems.
- Maintained version-controlled report artifacts and deployment pipelines using Git and Azure DevOps, supporting repeatable releases and production reporting stability.
Projects
Enterprise Business Analytics Dashboard
Tools Used: SQL, Power BI, Python, DAX
- Built end-to-end Power BI dashboards driven by SQL-based data models to surface business and financial metrics for decision-makers.
- Implemented Python-based data validation routines to ensure source-to-report consistency and flag anomalies before dashboard refreshes.
- Created reusable DAX measures and optimized visuals for performance to support interactive exploration by stakeholders.
Sales Analytics Dashboard
Tools Used: Power BI, SQL, KPI reporting
- Developed interactive sales reports tracking revenue, sales performance and customer KPIs with slicers and drill-throughs to support regional managers.
- Constructed dataset transformations in SQL to aggregate transactional data into business-friendly metrics and time-series comparisons.
- Designed dashboard layouts and visualizations to highlight trends and outliers for weekly sales reviews.
House Price Prediction
Tools Used: Python, scikit-learn, Regression modeling
- Performed exploratory data analysis and feature engineering on housing datasets to prepare inputs for regression models.
- Trained and evaluated regression models using scikit-learn, validated performance with cross-validation and reported model metrics to guide feature selection.
- Documented modeling process and results to demonstrate regression approaches and predictive capability for target pricing.
Education
University of Maryland, Baltimore County
M.S. Information Systems • 2024 – 2026
Sridevi Women's Engineering College
B.Tech. Information Technology • 2020 – 2024
Certifications
Microsoft Azure Developer Associate (AZ-204) — Microsoft
AWS Solutions Architect – Associate — Amazon Web Services
Programming Essentials in Python
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