Data Analyst Power Bi

SACHI MONNAPPA CHOKIRA

United States +1-747-***-**** ***************@*****.*** LinkedIn

SUMMARY

Data Analyst with 3+ years of experience solving business problems by transforming raw operational, sales, and customer data into actionable insights using Python, SQL, Power BI, and Tableau.

Proven success in building automated ETL pipelines and interactive dashboards to optimize marketing spend, monitor KPIs, and streamline reporting in cross-functional teams.

Skilled in data modeling, statistical hypothesis testing, A/B experiments, and cohort analysis to evaluate product performance and inform business decisions.

Adept at working with large-scale datasets from relational databases, CRMs, and cloud-based data warehouses (e.g., Snowflake, AWS), ensuring clean, reliable, and production-ready analytics.

Experienced in Agile teams collaborating with product, marketing, and engineering teams to deliver end-to-end data solutions with strong emphasis on scalability and accuracy.

SKILLS

Methodologies: SDLC, Agile/Scrum, Waterfall

Programming: Python, SQL (complex queries, joins, CTEs), SAS Statistical Analysis: Descriptive Statistics, Hypothesis Testing, A/B Testing, Correlation Analysis, Regression Modeling Libraries: Pandas, NumPy, Matplotlib, Seaborn, Pyplot, SciPy, Scikit-Learn Data Visualization: Tableau, Power BI (DAX), Looker, Advanced Excel (Pivot Tables, VLOOKUP, Power Query), KPIs ETL & Cloud: SSIS, Snowflake, CRM, SSRS, AWS

Databases: MySQL, NoSQL, PostgreSQL, PL/SQL, MS SQL Server, MS Access Other Skills: Git, GitHub, Jira, Visual Studio Code, Data Cleansing, Data Wrangling, Data Modeling, Predictive Modeling EXPERIENCE

Walgreens United States

Data Analyst January 2025 – Present

Built a Python-SQL pipeline to automate extraction and transformation of weekly promotional sales data from AWS S3 into Snowflake, improving reporting SLAs by 45%.

Designed Power BI dashboards for category-level sales trends, discount tracking, and margin contribution across 200+ retail locations.

Conducted statistical A/B testing to evaluate loyalty program experiments, identifying segments with a 17% higher retention uplift.

Created predictive models using Logistic Regression and XGBoost to flag at-risk customers based on recent purchasing behavior, helping the retention team reduce churn by 11%.

Partnered with product managers to define key engagement KPIs and integrated Looker dashboards to monitor user behavior across digital and in-store channels.

Wrote complex SQL queries (CTEs, window functions) to calculate year-over-year growth, driving pricing strategy for Q2 products.

Cleaned CRM and transaction data using Python (Pandas NumPy), improving campaign audience segmentation accuracy by 28%.

Conducted cross-functional sprint planning using Jira and Agile methodology, aligning analytics requests across marketing and operations teams; tracked backlog items and delivery velocity for improved stakeholder visibility.

Supported Regulatory & Compliance Reporting by defining project documentation workflows in SharePoint, ensuring audit-readiness and full traceability across 5+ projects.

Mindtree India

Data Analyst January 2021 – July 2023

Developed automated Excel dashboards with Power Query and DAX for daily performance tracking across 3 departments, reducing manual reporting time by 60%.

Wrote advanced PostgreSQL queries to analyze user interactions across a SaaS platform, delivering monthly retention and engagement reports to the product team.

Applied clustering algorithms (K-Means) to segment users by activity and value, helping shape personalized email campaigns with a 14% increase in click-through rates.

Supported marketing analytics by analyzing lead-to-conversion rates across paid campaigns using Tableau and SQL, optimizing ROAS

(Return on Ad Spend) by 20%.

Collaborated with cross-functional teams to build/test data quality rules, identifying pipeline bottlenecks; ensuring 99.2% data accuracy.

Utilized ETL pipelines via SSIS to consolidate CRM data, email marketing, and order management systems into a unified reporting layer.

Designed and published SSRS reports from PL/SQL queries to automate compliance tracking and finance reconciliation processes, reducing report preparation time by 50%.

Created forecasting models using ARIMA and Exponential Smoothing to predict monthly revenue trends and inventory needs.

Utilized MS Access to create a lightweight internal data repository and GUI interface for business users, enabling query execution without engineering dependencies and reducing ad hoc report requests by 35%. EDUCATION

Master of Science in Business Analytics August 2023 – May 2025 California State University, Northridge, California Bachelor of Engineering in Electronics & Communication August 2018 – August 2022 Nitte Meenakshi Institute of Technology, India

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