Data Analyst Power Bi

SUMA PEDDIREDDY

Data Analyst

IL • 312-***-**** • **************@*******.*** • LinkedIn

SUMMARY

Skilled as a Data Analyst having over 3+ years of experience specializing in data analysis, reporting automation, and business process optimization. Proficient in SQL, Python, Power BI, and Tableau for data visualization and actionable insights. Experienced in leveraging predictive analytics, statistical analysis, and machine learning techniques to support data-driven decision-making. Skilled in handling large-scale datasets using Big Data technologies such as Apache Hadoop, Apache Spark, and Kafka. Strong expertise in cloud platforms like AWS, Google BigQuery, and Azure for scalable data solutions. Adept at collaborating with cross-functional teams to define business requirements, automate data workflows, and implement efficient data governance practices.

SKILLS & OTHER

Languages & Data Tools: Python (Pandas, NumPy), SQL, R

Visualization & BI Tools: Power BI (DAX), Tableau, Excel (Pivot Tables, VLOOKUP)

Cloud Platforms: AWS (EC2, S3, Redshift, Lambda), Azure (Data Factory, Azure SQL), Google BigQuery

Big Data & ETL Tools: Apache Hadoop, Apache Spark, Apache Kafka, AWS Glue, Snowflake

Databases: PostgreSQL, MySQL, SQL Server, Azure SQL, Snowflake

Statistical & ML Techniques: Regression Analysis, Predictive Modeling, Time-Series Forecasting (ARIMA, Prophet), A/B Testing

Project & Agile Tools: JIRA, Confluence, Agile (Scrum), SDLC

Documentation & Testing: BRD, FRD, Use Cases, UAT Plans, Test Scripts

Collaboration & Productivity: Microsoft Office Suite, Teams, SharePoint PROFESSIONAL EXPERIENCE

BNY MELLON, IL, USA MAR 2025 – CURRENT

Data Analyst

Spearheaded the automation of data pipelines using Python and SQL, reducing financial reporting time by 25% and increasing data consistency across multiple platforms.

Conducted detailed data analysis of large transaction datasets, identifying key patterns and anomalies that enhanced fraud detection and transparency in financial reporting.

Developed interactive Power BI dashboards to monitor key performance indicators (KPIs), empowering senior management to make real-time data-driven business decisions.

Led the integration of diverse financial data systems, including SQL Server and Snowflake, into a centralized data warehouse, optimizing reporting and enhancing operational efficiency.

Utilized machine learning techniques such as regression analysis and predictive modeling to forecast financial trends, improving forecasting accuracy by 15%.

Collaborated closely with stakeholders to gather requirements for reporting tools, enhancing business processes through automation and ensuring alignment with organizational objectives.

Automated financial reconciliation processes, reducing manual effort by 40% and improving data accuracy across business units.

Actively participated in Agile Scrum ceremonies, contributing to sprint planning, backlog grooming, and timely feature delivery.

Developed detailed UAT test cases and led user acceptance testing (UAT) sessions to ensure that systems met business requirements and reduced post-deployment issues.

ACCENTURE, INDIA AUG 2021 – AUG 2023

Data Analyst

Engineered and managed end-to-end ETL pipelines using Apache Hadoop, Spark, and AWS Redshift, enhancing the efficiency and scalability of enterprise data warehousing.

Designed and deployed real-time dashboards with Power BI and Tableau, enabling executive teams to monitor key business metrics such as churn rate, revenue, and campaign ROI.

Integrated Apache Kafka for real-time data ingestion from multiple sources, improving analytics turnaround time and enabling on-the-fly decision-making.

Automated recurring reporting and data transformation tasks using Python (Pandas, NumPy), reducing manual effort and eliminating errors in monthly business reports.

Conducted advanced data cleansing, normalization, and validation across disparate systems using Python and SQL, improving reporting accuracy by over 30%.

Developed predictive models for customer retention, upsell targeting, and lifetime value forecasting using Scikit-learn and R, boosting marketing efficiency.

Performed A/B testing and statistical analysis to evaluate new feature rollouts and pricing strategies, translating results into actionable insights for product teams.

Built SQL-based reporting solutions using PostgreSQL and MySQL, optimizing query performance and enhancing insights delivery across financial and operations teams.

Utilized AWS services (EC2, S3, Redshift, and Lambda) to support scalable data workflows and real-time analytics pipelines.

Collaborated closely with business stakeholders and product managers to define KPIs and success metrics for analytics projects.

Led the creation of BRDs, FRDs, and use case documents, capturing functional requirements and aligning stakeholder expectations with technical outcomes.

Developed UAT plans and test scripts, coordinated with QA teams, and managed bug resolution cycles for analytics features and dashboards.

Participated in Agile ceremonies (scrum, retrospectives, sprint reviews), ensuring alignment between data delivery and sprint goals.

Conducted root cause analysis on anomalies and system issues, working with engineering teams to resolve data discrepancies and optimize pipelines.

Documented data dictionaries, ETL mapping documents, and process flow diagrams to improve team onboarding and long- term data governance.

Partnered with cross-functional teams across finance, marketing, and product to design and deliver ad hoc insights for quarterly business reviews.

Supported data migration and cloud adoption projects, including transformation of legacy ETL jobs to AWS-based pipelines. CIPLA, INDIA FEB 2021 – JUL 2021

Data Analyst Intern

Supported a sales analytics project by cleaning and merging data from 15+ regional distributors using SQL and Excel, standardizing reporting for inventory and prescription trends.

Built exploratory data analysis dashboards in Tableau to identify demand shifts for key respiratory and cardiovascular drugs across metro and rural markets.

Conducted time-series forecasting on seasonal medicine demand using Python (ARIMA, Prophet), providing actionable insights to improve monthly restocking strategies.

Assisted in automating regional sales performance reports using Python (Pandas, NumPy) and delivered executive summaries to 3 business units, reducing manual effort by 30%.

Collaborated with supply chain and inventory teams to map SKU-level consumption trends and visualize gaps in stock coverage using Power BI, supporting real-time alerts for critical inventory thresholds.

Participated in KPI definition sessions with senior analysts and helped document metrics for brand-level product uptake, aiding in early-stage marketing evaluation.

Contributed to ad hoc data requests and insight generation using MySQL, enabling stakeholder visibility into pricing variations and distributor performance.

PROJECTS

Retail Sales Forecasting & Inventory Optimization

Analyzed ~200K retail transactions using SQL and Python across product categories; applied ARIMA and Prophet for time- series forecasting by region and season.

Built interactive Tableau dashboards to visualize demand trends, stock-out risks, and restocking strategies, simulating a reduction in excess inventory.

Cloud-Based ETL & BI Pipeline for Student Performance

Built an ETL pipeline using Azure Data Factory, Python, and Azure SQL to process student grading and attendance data across academic terms.

Designed Power BI dashboards with DAX to monitor dropout risk, performance trends, and faculty impact, enabling informed academic interventions.

EDUCATION

Wichita State University, KS AUG 2023 – DEC 2024

Master’s in Business Analytics

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