Information Security Power Bi

CHAITANYA VARANASI

Glendale, AZ, *****, USA 480-***-**** ******************@*****.*** LinkedIn PROFESSIONAL SUMMARY

Seasoned professional with 8+ years of experience in Information Security, Data Engineering, and Analytics, specializing in designing secure, scalable, and audit-ready data ecosystems within highly regulated industries. Proven expertise in threat detection, data loss prevention, and compliance automation across GDPR, ISO, NIST, SOC/SOC 2, SIEM and HIPAA frameworks. Adept at integrating and operationalizing security telemetry from Microsoft Defender, Proofpoint, and CrowdStrike to strengthen detection capabilities and incident response. Skilled in architecting and maintaining robust data governance frameworks using Microsoft Purview, Azure Key Vault, and Sentinel, with a focus on access control, lineage tracking, and proactive DLP enforcement. Strong background in building modular, testable ETL pipelines and data models using SQL, Python, PySpark, Azure Data Factory, and Azure Synapse, AEP, AEM supporting advanced analytics and predictive modeling with Power BI and other BI platforms. Proficient in Git, Azure DevOps, and Agile delivery, with a track record of driving cross-functional data initiatives that enhance security posture, operational efficiency, and compliance readiness. Recognized for developing security-first data frameworks that align technical solutions with business risk, enabling real-time detection, audit compliance, and continuous improvement of security operations. EDUCATION

PGDM – Leadership through Analytics and Decision Sciences T A PAI Management Institute 2021 Relevant Coursework: Data Analytics, Data Science, AI, ML, Deep Learning, Information Security Bachelor’s of Engineering in Mechanical Andhra University 2015 TECHNICAL SKILLS

Cloud Platforms & Storage Microsoft Azure (ADLS Gen2, Synapse, Sentinel, Key Vault), AWS CloudWatch, MySQL, AEP

Programming & Scripting Python (pandas, NumPy, pyodbc, scikit-learn), SQL (T-SQL, Redshift, PostgreSQL, MySQL, HiveQL)

BI & Visualization Power BI, Tableau, Looker Studio, Microsoft Excel (Advanced) AI/ML & Advanced Tech Azure Databricks, ML Models, A/B Testing, Attribution Modeling Governance & Compliance

Tools

Microsoft Purview, AIP, M365 Compliance Center, Microsoft Defender, Endpoint, Proofpoint

Tools & Utilities Git, Azure DevOps, JIRA, Confluence, ServiceNow ETL & Workflow ADF, PySpark, Apache Airflow, REST APIs, Snowflake, Teradata Studio, Label Studio

Methodologies & Frameworks Agile (Scrum, SAFe, Kanban), Waterfall, CI/CD, DevSecOps Data Engineering & Analytics Data Extraction, Transformation, Cleaning, Mapping, Mining, EDA PROFESSIONAL EXPERIENCE

Information Security Engineer First American Client - First American 07/2022 - 04/2025

• Engineered and optimized scalable DLP-centric ETL pipelines using Azure Data Factory, Python, and PySpark, processing over 1 million structured and unstructured records daily from internal systems, audit logs, and endpoint protection platforms, enabling detection of 500+ potential data exfiltration incidents monthly.

• Developed a fully automated compliance-driven DLP incident reporting framework using Azure Data Lake Gen2 and Power BI, reducing manual compliance efforts by 60%, improving audit readiness, and accelerating incident triage by 40%.

• Designed and implemented advanced Power BI dashboards for real-time monitoring of DLP metrics— including policy detections, MIP labeling status, and rule enforcement—from Azure Sentinel and Microsoft Purview((Rule Match, Rule Undo, Auto Labeled files & Manual Labeled files, Policy detection), resulting in a 30% increase in reporting efficiency and a 25% faster escalation workflow.

• Created role-based, access-controlled dashboards offering granular visibility into DLP violations and anomalous file activities across 12 departments and 2,000+ users, contributing to a 35% reduction in time- to-detect (TTD) and 20% reduction in false positives for insider threat incidents.

• Automated metadata validation and schema enforcement with Python scripts, ensuring classification accuracy across Microsoft Purview, M365 Compliance Center, and Azure Information Protection; reduced misclassification by 40% and improved policy alignment audits by 50%.

• Enhanced detection engineering by developing custom log parsers and enrichment utilities in Azure Sentinel, normalizing over 2 million security events monthly from Microsoft Defender, Proofpoint, and CrowdStrike, which improved unified threat correlation and reduced log ingestion lag by 25%.

• Collaborated cross-functionally with Security Operations, Legal, and GRC teams to operationalize and automate DLP controls and compliance enforcement (HIPAA, ISO 27001, NIST 800-53, GDPR), achieving a 95% audit pass rate and contributing to a 30% reduction in compliance incident response times. Environment: ADF, ADLS, Sentinel, Purview, Power BI, Python (pandas, pyodbc), KQL, T-SQL, Defender, Endpoint, Azure Blob Storage, Proofpoint, Trainable Classifiers REST APIs, MS Excel, ServiceNow Trainee Apprentice Leader Mu-sigma Inc. Client - The Home Depot 08/2021 - 07/2022

• Responsible for planning, strategizing, implementing, and deploying campaigns such as Promo PAM, Consumer, HD Home Acquisition & Repurchasers, Special buy of the week for $150M revenue with close collaboration with marketing partners.

• Engineered Python-based ETL pipelines to unify data from store transactions, loyalty systems, and e- commerce interactions, reducing report generation time by 50%.

• Applied clustering techniques on purchase frequency and customer demographics to segment loyalty card holders and refine marketing outreach strategies.

• Created regression models to forecast foot traffic and sales revenue by department and location, improving forecast accuracy by 18%.

• Partnered with data science teams to evaluate A/B test results for digital and in-store offers, leading to a 12% increase in promotional ROI.

• Developed Power BI dashboards to present product-level analytics to merchandising managers, enabling data-driven stocking and layout decisions.

• Conducted cross-channel attribution analysis using SQL and Python to assess marketing campaign impact across TV, digital, and print media.

• Performed exploratory data analysis (EDA) using Pandas and Matplotlib to identify seasonal trends in customer behavior.

Environment: SQL (Redshift, MySQL), Python (Pandas, NumPy, Scikit-learn, Matplotlib), AEP, AEM,Power BI, MS Excel, Apache Airflow, HiveQL, Git, JIRA, Windows, GDPR Compliance Tools Associate Consultant - Data Engineer Capgemini Client - Alliance Bernstein 09/2019 - 08/2020

• Responsible for designing, executing, and continuously optimizing email-based marketing campaigns for major retail and financial clients including PLCC, CareCredit, and B2C credit card programs.

• Partnered with cross-functional product and campaign teams to define A/B testing frameworks, extract engagement metrics, and optimize conversion paths; uncovered a previously overlooked customer segment that led to a 15% increase in sales in Q2.

• Wrote complex SQL queries on Redshift and MySQL to extract marketing and transactional data for segmentation, personalized targeting, and multi-touch attribution analysis.

• Created Power BI dashboards to visualize real-time campaign performance across email open rates, click- through rates (CTR), and funnel drop-offs, driving data-backed strategy pivots.

• Utilized tools like MessageGears and Moveable Ink to automate personalized email content, ensuring dynamic rendering based on customer behaviors and preferences.

• Implemented data validation and pre-send checks through Python scripts, minimizing erroneous sends and increasing email delivery accuracy by 20%.

Environment: SQL (Amazon Redshift, MySQL), Python (Pandas, Regex), Power BI, MS Excel, JIRA, Agile Methodology, Windows

Senior Associate - Data Analytics Cognizant Technology Solutions Client - Facebook 02/2018 - 02/2019

• Collected, cleaned, and transformed over 500 million rows of structured and semi-structured data from Facebook’s internal SQL databases and APIs to power marketing performance dashboards.

• Built over 20 automated reports and dashboards in Power BI, reducing manual reporting time by 40% and enabling real-time tracking of campaign ROI, bounce rates, and funnel attrition.

• Designed and deployed UTM tagging strategies, Facebook Pixel implementations, and Google Tag Manager scripts, improving tracking accuracy and attribution across paid and organic marketing channels.

• Created predictive Python models for budget optimization, reach forecasting, and personalized content delivery—contributing to a 15% lift in campaign efficiency.

• Analyzed A/B testing results from email and landing page experiments, identifying patterns that improved CTR and conversions; directly contributed to a 12% increase in user engagement.

• Partnered with marketing, engineering, and data science teams to redefine campaign KPIs, increasing funnel measurement granularity and enabling more precise performance diagnostics. Environment: SQL (Redshift, PostgreSQL), Python (Pandas, NumPy, scikit-learn), Power BI, Facebook Pixel, Google Tag Manager, UTM Parameters, APIs, MS Excel, Jupyter Notebook, Git, Windows IT Analyst Intelenet Global Services (Serco) Client - Google 09/2016 - 02/2018

• Investigated and triaged sensitive content escalations using structured metadata, backend SQL log analysis, and internal moderation dashboards to assess risk, severity, and alignment with YouTube’s Community Guidelines.

• Collaborated cross-functionally with Trust & Safety, Legal, and Product teams to map policy workflows, document escalation protocols, and standardize decision-making criteria across surfaces like YouTube Search, Watch, and Comments.

• Wrote SQL queries to aggregate reviewer decision data, compute average SLA turnaround times, and analyze reviewer workload distribution, improving accuracy of case prioritization and reporting to executives.

• Analyzed metadata fields such as video tags, user reports, watch location, and timestamps to identify patterns in harmful content and automate flagging criteria for repeat abuse.

• Created visual dashboards using Google Sheets (with QUERY functions) and Looker Studio (formerly Data Studio)to highlight trends in policy violations by region, topic cluster, and content type. Environment: SQL (BigQuery), Google Sheets (QUERY functions), Looker Studio (Data Studio), YouTube Internal Tools (CRM, Escalation Dashboards), Google Workspace, Python (Pandas for audits), JIRA, Confluence, Windows

ACHIEVEMENTS

• Certifications: AZ-900 Fundamentals, AZ-500: Microsoft Azure Security Technologies

• Certifications: LeadPro: LeadPro is a simulation platform, which helps to accelerate the development of leadership skills. It is an engaging, challenging, and robust learning experience that stretches managers to confront complex, highly interwoven performance management and people management issues.

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