Rajesh Chandaluri
Senior Data Analyst • Plano, TX • r****************@applywizard.ai • +16******698 • drivetube.ai/•••••
Professional Summary
Senior Data Analyst with 3+ years of experience building operational and product analytics for telecommunications, financial services, and IT services organizations. Expert in SQL and Python-based data pipelines and in delivering self-service BI with Power BI and Tableau; experienced with Snowflake, Databricks, and Azure Data Factory for scalable reporting. Delivered analytics on hundreds of millions of records, improved dashboard performance and query efficiency, and instituted metric governance to ensure trusted KPIs for leadership reviews. Skilled at automating recurring reporting, performing source-to-target reconciliation, and applying anomaly-detection tooling to highlight unusual KPI movements. Comfortable owning end-to-end reporting lifecycle from requirements and data model design to testing, deployment, and stakeholder sign-off using JIRA and Confluence.
Technical Skills
Programming Language: Python,SQL
Databases: Snowflake,MySQL,CTEs,Window Functions
Data Engineering & Processing: Azure Databricks,User Acceptance Testing
Data Warehousing: Dimensional Modeling
Data Analysis & Visualization: Pandas,NumPy,Power BI,DAX,Power Query,Tableau,PivotTables,XLOOKUP,Formulas
Machine Learning & AI: Anomaly Detection
Data Integration & ETL: Azure Data Factory,ETL
Compliance & Governance: Data Quality,Data Governance
Project Management & Collaboration: Jira,Confluence
Process Modeling & Documentation: Requirements Gathering
Quality Assurance & Compliance: Root Cause Analysis
Market Research & Consumer Insights: Customer Segmentation
Work Experience
Verizon
Irving, TX
Senior Data Analyst
Jul 2025 – Present
Delivered analytics for a major US telecommunications provider supporting customer, product and network operations reporting.
Tech Stack: SQL, Python, Databricks, Power BI, DAX, Power Query, Power BI Dataflows, Power BI Copilot, Confluence, JIRA
- Led reporting delivery for multiple product and customer operations teams by translating business requirements into SQL datasets and Power BI semantic models.
- Built ETL workflows in Databricks using SQL to process 200M+ customer and usage records for recurring operational reports.
- Accelerated Power BI dashboard response times by 25% through query tuning, model refactor, and DAX optimization.
- Automated recurring reporting with Power Query, Power BI Dataflows, and Python, freeing analysts to focus on investigations and ad-hoc analysis.
- Implemented SQL reconciliation and data-profiling checks to identify incomplete records and remove stale metrics from production dashboards.
- Applied Power BI Copilot and Python-based anomaly detection to surface and summarize unusual KPI movements for leadership review.
- Managed metric governance, refresh dependencies, and access controls in Confluence and JIRA to ensure traceable dashboard changes and approvals.
Capital One
Plano, TX
Data Analyst II
Aug 2024 – Jun 2025
Supported portfolio, risk, marketing and product analytics at a US financial services company, standardizing measures for reporting.
Tech Stack: Snowflake, SQL Server, MySQL, Power BI, Tableau, DAX, Power Query, Azure Data Factory, Python, Pandas, NumPy, JIRA, Confluence
- Designed eight Power BI and Tableau dashboards using SQL, DAX, and Power Query for Risk, Marketing, Product, and Operations stakeholders.
- Tuned Snowflake, SQL Server, and MySQL queries using CTEs and window functions, cutting scheduled extraction time by 30%.
- Consolidated customer, transaction, and product data into Snowflake reporting tables to create consistent measures used across BI tools.
- Performed Python analyses with Pandas and NumPy to characterize customer behavior and product usage for targeted campaigns and product decisions.
- Hardened Azure Data Factory pipelines with source-to-target checks and transformation reviews to improve refresh reliability and detect schema drift.
- Validated 10M+ transaction records with SQL profiling and source-total reconciliation to prevent calculation errors in risk and portfolio reports.
- Coordinated KPI sign-off, UAT, defect resolution, and release evidence in JIRA and Confluence to control production publication.
- Investigated funnel movement and campaign response with SQL and Python to guide marketing targeting and roadmap prioritization.
Kyndryl India Pvt. Ltd.
Hyderabad, India
Data Analyst
Sep 2021 – Jul 2022
Provided analytics and operational reporting across IT services business units, combining service, cost and delivery data for SLA reviews.
Tech Stack: Power BI, Tableau, Python, Pandas, SQL, Power Query
- Managed Power BI and Tableau reporting across multiple business units by integrating service, resource, cost, and delivery datasets into unified views.
- Streamlined SQL queries through join refinement and filter tuning, cutting report processing time by 25%.
- Automated file consolidation and validation with Python, Pandas, and Power Query, reducing spreadsheet-related errors and manual effort.
- Built reporting-ready datasets through ETL workflows and star-schema design to enable consistent cross-functional comparisons.
- Validated 750K+ incident, service-request, resource, and delivery records using SQL profiling and reconciliation checks for dashboard accuracy.
- Mapped SLA, staffing, and cost measures to agreed definitions with service delivery managers to shape Power BI and Tableau operational views.
- Analyzed SLA breaches and cost variances via SQL and root-cause analysis to prioritize corrective actions.
IBM India Pvt. Ltd.
Hyderabad, India
Junior Data Analyst
Feb 2021 – Aug 2021
Supported infrastructure, availability, capacity and backup analytics for enterprise IT operations and support teams.
Tech Stack: Tableau, SQL, Excel, PivotTables, XLOOKUP
- Built six Tableau dashboards from infrastructure, availability, capacity, and backup data to improve operational visibility.
- Configured near-real-time Tableau views with SQL-prepared datasets and scheduled refreshes, shortening issue-detection time by 20%.
- Validated 250K+ infrastructure and data-protection records through SQL profiling and reconciliation checks to ensure report reliability.
- Prepared recurring Excel reports with PivotTables, XLOOKUP, and advanced formulas to support delivery managers' operational reviews.
- Tested calculations, drill-down paths, refresh schedules, and user access before publishing dashboards through Tableau Server.
- Mapped infrastructure-health and capacity thresholds into Tableau filters and threshold views to isolate systems behind operational exceptions.
Tech Mahindra
Hyderabad, India
Data Analyst Intern
Nov 2020 – Jan 2021
Supported data-quality and reporting tasks for IT services analytics during a short-term internship.
Tech Stack: Python, Pandas, SQL, Tableau, Excel
- Implemented Python and Pandas validation checks to identify missing values, duplicates, and invalid formats, increasing reporting accuracy by 15%.
- Standardized 75K+ operational records using SQL and Python to provide clean datasets for recurring reporting and analysis.
- Supported developing five Tableau and Excel dashboards using PivotTables and filters to surface category trends and exceptions.
- Created reusable SQL queries to shorten recurring data-extraction time and accelerate the start of analysis.
- Explored distributions and unusual values with Pandas, NumPy, and Tableau to surface patterns for senior analyst investigation.
- Refined Tableau and Excel layouts based on analyst and business-user feedback to improve interpretability and filter usability.
Projects
Product Usage and Retention Analytics Platform
Tools Used: Snowflake, Dimensional Modeling, SQL, Python, Power BI, Tableau, DAX
- Structured customer, subscription, and product-event data in Snowflake using dimensional modeling and star schemas to create reusable reporting tables.
- Analyzed activation funnels, feature adoption, retention cohorts, and churn movement with SQL and Python to identify points of engagement decline.
- Designed Power BI and Tableau dashboards with DAX measures, cohort matrices, and drill-down filters to inform product roadmap and retention work.
U.S. Apartment Rental Market Analytics
Tools Used: Python, Pandas, NumPy, SQL, Tableau, Excel
- Cleaned and transformed 100,000+ rental records with Python and Pandas to produce a validated dataset for cross-city comparison.
- Examined pricing distributions, regional trends, and amenity associations through exploratory and statistical analysis to identify pricing drivers.
- Presented interactive Tableau dashboards and Excel summaries enabling users to filter markets, evaluate affordability, and review rental trends.
Education
Wichita State University
Master of Science in Business Analytics • Wichita, KS • Aug 2022 – Apr 2024
KL University
Bachelor of Technology in Computer Science and Engineering • Vijayawada, India • Jun 2016 – Apr 2020
Certifications
Google Data Analytics Professional Certificate — Coursera
Microsoft Power BI Data Analyst Professional Certificate — Coursera
Certified Tableau Data Analyst — Tableau
Complete Guide to Generative AI for Data Analysis and Data Science
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