Data Analyst Quality

Vijay Jagadesh Narisetty Data Analyst

Contact: +1-719-***-**** Email: *****@*********.*** Location: Denver, CO SUMMARY

Analytical and detail-oriented Data Analyst with 3+ years of experience transforming complex data into actionable insights to support strategic decision-making across procurement, finance, and manufacturing domains.

Adept at leveraging SQL, Python, Tableau, and PySpark to extract, process, and visualize data while driving measurable business value in high-volume data environments.

Skilled in building intuitive dashboards, forecasting models, and automated ETL pipelines that improve data quality, reduce reporting time, and support executive-level decision-making.

Proficient in handling datasets exceeding 10 million records, identifying trends, anomalies, and process gaps to optimize operations and enable cost savings through automation and compliance.

Strong communicator with a track record of collaborating cross-functionally, leading data-driven initiatives, and delivering insights that enhance efficiency, reduce expenses, and influence organizational strategy. SKILLS

Languages: Python, R, SQL, T-SQL, MySQL, PostgreSQL Libraries: Pandas, NumPy, Matplotlib, Seaborn

Big Data: Hadoop, Hive, Spark, PySpark, Spark SQL

ETL Tools: Apache Airflow, AWS Glue, Talend, SSIS

Databases: SQL Server, PostgreSQL, MySQL, MongoDB

Visualization: Tableau, Excel (Pivot Tables, VLOOKUP, Charts)

Tools: Git, GitHub, Docker, Kubernetes

IDEs: Jupyter Notebook, VS Code, PyCharm

Methodologies: Agile, Scrum, SDLC

EXPERIENCE

Coupa Software USA Data Analyst Jan 2024 - Current

Developed KPI Tableau dashboards to enhance procurement transparency, reducing manual reporting by 40% and improving spend visibility by 25% for strategic sourcing initiatives.

Automated SQL-based reports to analyze supplier performance, enabling 15% cost reduction across procurement functions by identifying inefficiencies and optimizing vendor selection.

Built automated workflows using Apache Airflow and AWS Glue, streamlining data pipelines and saving 33% of manual data extraction and processing time.

Utilized Pandas and NumPy to clean and transform 80% of datasets, improving data quality and accuracy by over 20% for downstream reporting and decision-making.

Created R-based forecasting models to predict procurement trends, reducing overspending by 12% and enhancing accuracy of financial planning for the finance department.

Leveraged PySpark to analyze 10M+ transaction records, detecting contract violations and saving $500K annually by optimizing vendor negotiations and compliance.

Led cross-functional GAP analyses that uncovered inefficiencies in expense workflows, implementing automation that doubled processing speed across procurement departments.

Presented actionable insights to executive leadership, directly influencing decisions that contributed to $2M in procurement savings and increased vendor accountability.

One Advanced, India Data Analyst Jan 2020 - Jul 2022

Engineered ETL pipelines using Apache Airflow and AWS Glue, reducing ETL time by 40% and improving data reliability across procurement and manufacturing departments.

Performed SQL, Hive, and PySpark queries on 10M+ record datasets, uncovering actionable trends that improved operational efficiency by 20% for global clients.

Built 15+ dashboards in Tableau and Excel to visualize key KPIs, cutting reporting time in half and enhancing team collaboration and strategic alignment.

Migrated legacy data into PostgreSQL and MongoDB systems, improving data consistency and reducing query times by 60% through modernized database architecture.

Created churn prediction models in Python using Pandas and NumPy, improving accuracy by 25% and increasing customer retention rates by 10%.

Implemented big data pipelines on Hadoop clusters, enabling near real-time decision-making by improving data velocity by 30% in manufacturing environments.

Conducted anomaly detection and root cause analysis using R, reducing risks and preventing revenue loss of $9M across financial transaction systems.

Supported stakeholder reporting initiatives with actionable dashboards and visualizations, improving transparency and enabling data-driven decisions across finance and operations. EDUCATION

Master of Science: Business Analytics May 2024

University of Colorado Denver – Denver, CO

Bachelor of Technology: Mechanical Engineering May 2020 JNTUK, India

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