Divya Sri Vakkala
Data Analyst • United States • d***************@gmail.com • +14******029 • linkedin.com/••••• • drivetube.ai/•••••
Professional Summary
Data Analyst with 5+ years of experience specializing in data analytics, ETL development, data engineering, business intelligence, and statistical analysis. Proven expertise in SQL, Python, Databricks, Snowflake, Power BI, Tableau, and AWS, with a track record of improving operational efficiency by 70% through ETL automation. Skilled at transforming complex datasets into actionable insights, optimizing data quality, and delivering scalable analytics solutions that support data-driven business decisions.
Technical Skills
Programming Languages: Python,R
Databases & Data Warehousing: SQL,MySQL,PostgreSQL,Oracle,MongoDB,Snowflake,Data Modeling
Cloud Platforms & Data Engineering: AWS,Amazon RDS,Databricks,dbt,Data Ingestion,Data Transformation,Data Cleaning,Data Validation,Data Reconciliation,Data Migration,Data Integration,ETL Pipeline
Data Analysis & Machine Learning: Pandas,NumPy,Scikit-Learn,Exploratory Data Analysis,Trend Analysis,Root Cause Analysis,Data Profiling
Data Visualization & Business Intelligence: Power BI,Tableau,Excel,Matplotlib,Seaborn,AWS QuickSight,KPI Reporting
Version Control & Collaboration: Git,JIRA
Methodologies: Agile,Scrum,Waterfall,SDLC
Work Experience
Allstate
Data Analyst
July 2023 – Present
Major U.S. insurer; engineered data pipelines and analytics assets that power policy, claims and customer reporting for faster, more accurate insurance insights.
Tech Stack: Databricks, ETL, SQL, Python, Power BI, Tableau, Data Validation, Data Reconciliation, Data Cleansing, Data Warehousing, Agile
- Engineered ETL pipelines in Databricks to integrate policy, claims, and customer datasets, reducing data processing time by 35% and improving analytics readiness for insurance reporting and decision-making.
- Developed Power BI and Tableau dashboards to monitor claims performance, policy retention, loss trends, and operational KPIs, enabling business stakeholders to make data-driven decisions.
- Optimized data validation, reconciliation, and cleansing frameworks using SQL and Python, increasing reporting accuracy by 12% while strengthening enterprise data quality and integrity.
- Collaborated with cross-functional teams to translate analytical requirements into user stories, support sprint planning and backlog refinement, and accelerate project delivery timelines.
- Leveraged Databricks, SQL, Python, ETL, and Data Warehousing technologies to streamline reporting workflows, automate data preparation processes, and improve reporting efficiency by 30%.
University of North Texas
Teaching and Research Assistant
Aug 2022 – May 2023
Public research university; supported graduate big data, AI and ML instruction and research by preparing datasets, mentoring students and validating analytical work.
Tech Stack: Python, SQL, Data Analysis, Data Cleaning, Data Transformation, Data Visualization, Pandas, NumPy, Scikit-Learn, Predictive Modeling, Exploratory Data Analysis
- Facilitated graduate-level Big Data, AI, and Machine Learning coursework by mentoring students on Python- and SQL-based data analysis projects, improving assignment completion rates by 20%.
- Instructed students on data cleaning, transformation, and exploratory data analysis techniques using real-world datasets, strengthening analytical and data interpretation capabilities.
- Validated SQL queries, Python notebooks, and data visualizations to ensure analytical accuracy, reducing submission errors by 15% through structured review processes.
- Partnered with faculty members and supported graduate students by preparing datasets, developing lab exercises, and enhancing hands-on learning experiences.
- Implemented machine learning models using Python, Pandas, NumPy, and Scikit-Learn for academic research initiatives, improving predictive accuracy by 25% and advancing model effectiveness.
Cognizant Technology Solutions
Program Analyst
Oct 2021 – Aug 2022
Global IT consulting firm; delivered enterprise data engineering and analytics solutions that streamlined ETL, monitoring and KPI reporting for client operations.
Tech Stack: SQL, Statistical Analysis, Exploratory Data Analysis, ETL, Snowflake, Data Ingestion, Data Transformation, Tableau, KPI Reporting, Data Monitoring
- Analyzed complex operational and business datasets using SQL and statistical techniques, uncovering trends and insights that improved decision-making across many business functions.
- Evaluated exploratory data analysis results across large-scale datasets to identify process inefficiencies and recommend data-driven improvements that enhanced operational performance.
- Automated ETL workflows in Snowflake by streamlining data ingestion and transformation processes, reducing manual effort and improving operational efficiency by 70%.
- Coordinated with cross-functional stakeholders across data engineering, reporting, and business teams to resolve over production defects and strengthen data reliability.
- Developed interactive Tableau dashboards and automated SQL-based monitoring solutions to track 20+ KPIs, improving issue resolution efficiency and accelerating business reporting.
UWorld LLC
Data Analyst
Aug 2020 – Sep 2021
Company with substantial inventory operations; built data workflows, warehouses and dashboards to enhance inventory visibility, integrity and operational decision-making.
Tech Stack: SQL, Data Extraction, Data Migration, Data Integration, Data Warehousing, Data Cleansing, Python, Power BI, Pandas, NumPy, Matplotlib, Scikit-Learn
- Constructed SQL-based data extraction workflows across inventory databases, reducing data retrieval time by 30% and accelerating operational decision-making.
- Performed data migration, integration, warehousing, and cleansing activities across inventory systems, ensuring accurate and reliable data throughout the data lifecycle.
- Strengthened data integrity challenges by developing SQL- and Python-based reconciliation frameworks, improving consistency and accuracy across inventory datasets by 25%.
- Partnered with inventory managers, business users, and reporting teams to translate data requirements into analytical solutions, improving visibility into inventory performance and trends.
- Designed Power BI dashboards and Python-based visualizations using Pandas, NumPy, Matplotlib, and Scikit-Learn, enhancing reporting efficiency by 25% and supporting data-driven planning.
Education
University of North Texas
Master of Science in Data Engineering • Aug 2022 – May 2024
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