Data Analyst Power Bi

SAI DATTA KUMAR REDDY PANTHULA

Location: TX Phone: 940-***-**** Email: ****************************@*******.*** LinkedIn Summary

Data Analyst with over 3 years of experience delivering end-to-end data solutions across marketing, financial, and pharmaceutical domains. Proficient in building ETL pipelines, designing analytical datasets, and developing interactive BI dashboards to enable rapid, data-driven decision-making. Skilled in SQL, Python, and cloud data platforms (Snowflake, BigQuery, Azure Data Lake) for high-volume data processing, with proven success in transaction monitoring, anomaly detection, and fraud prevention. Adept at collaborating with cross-functional teams, implementing data governance, and aligning analytics capabilities with business objectives for measurable impact. PROFESSIONAL EXPERIENCE

EPSILON USA

Data Analyst Aug 2025 – Present

Designed and maintained Snowflake and BigQuery analytical datasets to support marketing performance analysis on 50M+ consumer behavior records, enabling segmentation queries to be completed in under 5 minutes.

Developed dbt and Apache Airflow workflows to refresh and transform multi-source marketing data, reducing manual reporting preparation by 30+ hours/month and ensuring consistent data availability.

Created interactive Tableau, Power BI, and MS Excel dashboards with row-level security, providing real-time campaign insights to 5 regional teams and improving decision-making speed for marketing managers.

Applied Python (PySpark) and SQL in Databricks to clean, standardize, and validate streaming data from Apache Kafka, reducing data quality issues by 12,000+ malformed events/month.

Led the migration of historical campaign datasets from AWS S3 to Snowflake, optimizing analytical storage by removing ~500GB of redundant or outdated files.

Collaborated with marketing analytics teams to incorporate attribution model outputs into Tableau, influencing budget allocation strategies for $25M+ in annual advertising spend.

Facilitated cross-department KPI alignment workshops, leveraging Agile methodology, resulting in 40+ new active dashboard users within the first month of rollout.

Presented quarterly Tableau and Power BI reporting enhancements to senior leadership, aligning analytics capabilities with the company’s BI modernization roadmap.

NTT DATA INDIA

Information System Analyst May 2021 – July 2023

Architected end-to-end SSIS ETL workflows to consolidate data from 12+ financial and operational systems into SQL Server, accelerating month-end reporting cycles by 3 business days through streamlined data integration.

Engineered Python pipelines integrated with AML platforms to analyze 250K+ daily financial transactions, detecting suspicious patterns in real time and initiating alerts that averted $1.2M+ in potential fraudulent activity.

Designed and deployed enterprise-grade Tableau dashboards for finance, operations, and compliance teams, enabling drill-down analytics on 5 regional datasets and reducing manual consolidation time by 20+ hours/month.

Developed robust data cleaning processes in Python to validate and normalize pre-load datasets, eliminating anomalies in 250K+ transactions/day and resolving 700+ reconciliation discrepancies annually. Orchestrated large-scale data migration from on-premise SQL Server and Oracle systems to Azure Data Lake, transferring 2TB+ of historical data with zero loss and full audit traceability.

Modeled and optimized SQL Server warehouse schemas using indexing strategies and partitioning, improving execution times by 40–50 seconds on high-volume reconciliation queries.

Collaborated with BI teams to redesign Tableau dashboards, implementing parameter controls, calculated fields, and optimized extracts, cutting refresh times from 4 hours to 45 minutes and improving stakeholder adoption.

Integrated Azure DevOps into ETL and dashboard release pipelines, establishing CI/CD workflows that reduced deployment errors by 7 incidents/year and enhanced delivery reliability for business-critical reports. CIPLA INDIA

Information System Analyst Apr 2020 – Apr 2021

Engineered SQL Server queries and stored procedures to cleanse and structure 1.2M+ pharmaceutical batch records, enabling regulatory compliance checks within 48 hours and improving audit readiness.

Designed interactive Tableau dashboards visualizing QA pass rates, defect trends, and production throughput, accelerating plant manager decision-making by 3 hours per batch cycle.

Developed Python automation scripts to clean sensor and lab datasets, removing 18,000+ duplicate or inconsistent records across 6 manufacturing facilities.

Migrated historical manufacturing datasets from Excel and legacy ERP exports into centralized SQL Server warehouses, creating a single source of truth for compliance, QA, and operations teams.

Consolidated procurement and supply chain metrics into Power BI reports, reducing raw material shortage resolution time by 12 days annually and improving cross-department visibility.

Led Tableau training workshops for 8 analysts, standardizing visualization templates, filters, and reporting practices for operational metrics.

Adani INDIA

Data Analyst Intern Dec 2019 – May 2020

Developed and implemented Python scripts to automate data cleaning, preprocessing, and analysis tasks, which reduced data processing time by 40% and improved efficiency in data analysis processes, streamlining workflows for the data analytics team.

Utilized SQL queries to retrieve, manipulate, and analyze data stored in SQL Server databases, ensuring high data integrity and accuracy that supported reliable business analytics.

Mastered advanced SQL techniques, including joins and group by queries, to efficiently merge and aggregate data across multiple tables, providing crucial support for complex data analysis and enhancing team decision-making processes.

Developed interactive and visually appealing dashboards and reports using Tableau, enabling stakeholders to easily comprehend key findings and trends, which facilitated informed decision-making.

Applied data cleaning and wrangling techniques using Python and SQL to preprocess raw data, addressing missing values, outliers, and inconsistencies, which resulted in a 15% increase in data reliability for subsequent analyses.

Increased productivity by 30% by automating reporting processes in MS Excel using advanced features like Pivot Tables and Chart. TECHNICAL SKILLS

Programming Language: Python, SQL, R

Databases & Warehousing: Snowflake, BigQuery, SQL Server, Oracle, Azure Data Lake, Databricks Libraries: NumPy, Pandas, Matplotlib, Scikit-learn. Data Visualization & Reporting: Tableau, Power BI, MS Excel (Pivot Tables, Macros), Row-Level Security, DAX Big Data & Cloud Skills: Hadoop, Apache Spark, Snowflake, Apache Airflow. Data Engineering & ETL: SSIS, dbt, Apache Airflow, Data Wrangling, Data Warehousing, Schema Optimization, AML Analytical Skills: Data Mining, Statistical Modeling, Hypothesis Testing, Problem solving. Methodologies: Agile, Waterfall, Git, GitHub, Azure DevOps Statistical Analysis & Modeling: Data Mining, Statistical Modeling, Hypothesis Testing, Logistic Regression Compliance & Governance: Data Governance, Regulatory Compliance (GMP, ISO), Risk & Fraud Monitoring. EDUCATION

University of North Texas Denton, TX

Master of Advanced Data Analytics Aug 2023- May 2025 GITAM University Hyderabad, India

Bachelor of Technology in Computer Science and Engineering Jul 2016 – Sep 2020 PROJECTS

Crime Pattern Forecasting and Hotspot Detection

● Performed comprehensive spatial-temporal crime analysis on 1M+ records from the Los Angeles crime database using Python

(Pandas, NumPy), SQL, and ArcGIS/QGIS for geospatial data handling.

● Applied geospatial clustering techniques (DBSCAN, K-Means) and time-series forecasting models (ARIMA, Prophet) to identify high-risk areas and predict crime patterns across time intervals.

● Conducted statistical analysis and data wrangling to detect trends in crime occurrence by time, location, and type, supporting evidence-based policing strategies.

Statistical Analysis of Hotel Booking Trends

● Analyzed three years of hotel reservation data using Python (Pandas, NumPy, Matplotlib, Seaborn) and SQL to uncover booking patterns, customer behaviors, and seasonal trends.

● Built predictive models in Scikit-learn to identify key drivers of booking cancellations, including lead times, room preferences, and customer type, improving forecast accuracy for cancellations.

● Conducted data visualization in Tableau and Power BI to present findings on booking patterns, guest demographics, and high- demand periods, aiding strategic planning.

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