Data Analyst Power Bi

RAVI TEJA ATHULURI

Dallas, TX +1-430-***-**** ********.*********@*******.*** LinkedIn

SUMMARY

Data Analyst with 3.5+ years of experience in healthcare, finance, and technology, focusing on ETL pipelines, data warehouses, and real-time data processing using Python, SQL, Apache Spark, SSIS, and Azure Data Factory. Skilled in cloud platforms such as AWS, Azure, and GCP for large-scale data integration and analytics. Experienced in building dashboards with Power BI and Tableau, ensuring data quality and compliance frameworks, and applying predictive modeling for operational and business insights. Proficient in SQL Server, Snowflake, PostgreSQL, and Oracle with strong emphasis on query optimization and automation to improve performance and reliability.

PROFESSIONAL EXPERIENCE

McKesson TX, USA

Data Analyst Aug 2025 – Current

Built and optimized data pipelines using Apache Spark and Snowflake, processing over 20 million healthcare transactions monthly, while generating automated KPI dashboards in Power BI to support supply chain and pharmacy operations.

Implemented data lineage, validation, and monitoring frameworks using Apache Airflow, Datadog, and SQL, reducing ETL pipeline failures by over 30 incidents per quarter and enabling accurate ad-hoc reporting and trend analysis for operational teams.

Collaborated with cross-functional teams to integrate FHIR and HL7 healthcare datasets, applying Python, SQL, and Excel- based analytics to standardize, enrich, and visualize data, producing actionable insights for reporting and predictive analytics initiatives.

Truist Bank TX, USA

Data Engineer Aug 2024 – Jul 2025

Engineered ETL pipelines using Azure Data Factory and PySpark, processing over 12 million transactional and financial records monthly, supporting predictive modeling and ML workflows for credit risk and customer analytics.

Designed and maintained data lake and warehousing solutions in Azure Synapse and Snowflake, consolidating 8+ structured and semi-structured banking datasets, reducing data retrieval time from 4 hours to 45 minutes for AI-driven risk analysis.

Automated feature engineering and data preprocessing workflows for ML models using Python, Pandas, and SQL, cleaning over 18,000 anomalies quarterly, improving model accuracy for customer segmentation and fraud detection initiatives.

Built interactive dashboards in Power BI and Tableau, visualizing KPIs for ML pipelines, model performance metrics, and predictive insights, tracking over 50 metrics across 6 business units to guide executive decision-making.

Migrated 5 TB of on-premise SQL and Oracle data to Azure Cloud, leveraging Blob Storage, Data Lake, and Azure Functions, enabling real-time AI model scoring and analytics with zero downtime.

Developed predictive credit risk and churn models using Python, PyCaret, and Spark MLlib, integrating multiple datasets, generating actionable reports that influenced $10M+ portfolio management and risk mitigation decisions.

Implemented data governance and ML model lineage tracking with Collibra and Azure Purview, cataloging 3,000+ tables/views, ensuring regulatory compliance and reproducibility of ML pipelines.

Mentored 4 junior engineers and analysts on SQL optimization, Python/ML scripting, data modeling, and dashboard design, reducing ETL development time by 100+ hours per quarter and improving ML pipeline efficiency. Dell Technologies India

Data Analyst Jan 2020 – Jul 2022

Developed automated dashboards in Tableau, Power BI, and SSRS, consolidating over 10 million rows of sales and customer data, enabling regional managers to monitor KPIs and improve decision-making for 12 business units.

Conducted data cleansing, transformation, and enrichment using Alteryx, SQL, and Excel Power Query, correcting 20,000+ inconsistent records across CRM and ERP systems, improving reporting accuracy and operational efficiency.

Performed trend analysis, regression modeling, and forecasting on product sales using R, Excel, and hypothesis testing, generating actionable insights that influenced $3M+ in quarterly inventory and supply chain allocation.

Implemented anomaly detection and KPI monitoring frameworks using Python and SQL, identifying 1,500+ irregular transactions monthly, enhancing data integrity and operational reporting reliability.

Collaborated with cross-functional teams to produce weekly, monthly, and quarterly reports using PowerPoint, Looker, and Excel dashboards, delivering insights on customer behavior, product adoption, and operational efficiency for executive stakeholders.

Designed ad-hoc analytical models and data visualizations using pivot tables, advanced Excel formulas, statistical functions, and Power BI, providing quick insights on customer churn, campaign performance, and sales growth across 5 product lines.

Standardized data documentation, KPI dashboards, and reporting templates, reducing report preparation time by 30 hours per month, ensuring consistency, audit-readiness, and alignment with business goals.

Mentored 2 junior analysts on SQL queries, Tableau and Power BI visualization, Excel modeling, and data storytelling techniques, increasing team efficiency and reducing report turnaround time by 25% per cycle. TECHNICAL SKILLS

Programming & Scripting: Python (Pandas, NumPy, Matplotlib, Seaborn), SQL, R (dplyr, ggplot2, tidyverse), Shell Scripting, Scala ETL & Data Processing: Apache Airflow, SSIS, PySpark, Pandas, Data Cleaning, Transformation, Validation, Feature Engineering Databases & Data Warehousing: SQL Server, Snowflake, PostgreSQL, MySQL, Oracle, BigQuery, Data Warehouses, Star Schema Cloud Platforms: AWS (S3, Redshift, Lambda, Glue), Azure (Data Lake, Synapse, Functions, Data Factory), GCP Data Analysis & Visualization: Power BI, Tableau, Google Data Studio, Excel (Pivot Tables, Power Query, VLOOKUP), SAS, SSRS Machine Learning & Analytics: Scikit-learn, TensorFlow, PyTorch, Predictive Modeling, Anomaly Detection, ML Model Deployment Automation & Orchestration: CI/CD Pipelines, Airflow DAGs, Git (GitHub, GitLab), Cron/Step Functions, Docker, Kubernetes, Helm Monitoring & Performance: Query Optimization, Data Pipeline Monitoring, Log Analytics, CloudWatch, Azure Monitor, Prometheus Collaboration & Governance: Agile (Scrum, Kanban), JIRA, Confluence, Data Governance, Documentation, Data Quality Assurance EDUCATION

Texas A&M University Commerce, TX, USA

Master of Science in Computer Science Engineering May 2024 Indian Institute of Technology (IIT) Roorkee India B.Tech + M.Tech in Electronics and Communication Engineering PROJECTS

Dec 2019

E-Commerce Transaction Analytics using Hadoop

● Ingested and processed 10M+ e-commerce transaction records into HDFS using Sqoop and cleaned data using MapReduce and Pig scripts, ensuring accuracy and consistency for downstream analysis.

● Queried datasets with HiveQL and created Tableau dashboards to identify top-selling products, seasonal trends, and customer purchasing patterns, enabling data-driven business decisions. Workforce Insights Dashboard

● Extracted and transformed HR datasets from multiple sources using SQL ETL pipelines, cleaning and standardizing 500K+ employee records for analysis.

● Built interactive Power BI dashboards to visualize attrition trends, department-wise turnover, and key factors influencing employee retention, enabling data-driven HR strategies.

CERTIFICATIONS

● Google Advanced Data Analytics

● MSME Azure Certification

● MSME Python Developer

● Ataccama ONE

● DQG Consumer Certification

● Reltio Data Steward Foundation

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