Data Analyst

Ravichandra Lakkappa

+1-805-***-**** Thousand Oaks, CA ****************@*****.*** LinkedIn Github SUMMARY

Data Analyst with 5+ years of experience building scalable analytics workflows, data pipelines, and stakeholder-facing reporting solutions. Strong expertise in advanced SQL (Snowflake, CTEs, window functions) and Python (pandas, NumPy) for ETL, data validation, and automated reporting. Proven ability to analyze structured and semi-structured data across cloud data warehouses and operational systems to support e-commerce, sales, operations, and finance analytics. Experienced partnering with cross-functional teams to define metrics, improve data quality, and deliver actionable business insights.

TECHNICAL SKILLS

• Languages & Analytics: Python (pandas, NumPy), Advanced SQL (CTEs, window functions, performance optimization)

• Data Platforms & Databases:Snowflake, SQL Server, PostgreSQL, AWS (S3, EC2), NoSQL concepts

• Data Engineering & Analytics: ETL / ELT Pipelines, Data Validation, Automated Reporting, Data Quality Frameworks, Performance Tuning, KPI Design

• Business Intelligence & Visualization: Power BI (DAX, data modeling, scheduled refresh), Excel, PowerPoint

• Version Control & Delivery: Git, GitHub, CI/CD fundamentals, Agile (Scrum), Jira, Confluence

• AI-Assisted Analytics: GitHub Copilot, ChatGPT (SQL optimization, analysis acceleration, documentation) WORK EXPERIENCE

• Data Analyst, Pro-Tek Consulting Aug 2024 – Present

Partner with data engineers to define requirements and support CI/CD-enabled analytics workflows, ensuring reliable deployment of SQL queries, reports, and dashboards (Power BI) across environments.

Built and maintained Snowflake-based analytics workflows using complex SQL (CTEs, window functions) to support sales, operations, and finance reporting.

Developed production Python scripts using Pandas/NumPy for ETL, validation, and automated reporting, analyzing multi-source JSON datasets for operational and e-commerce analytics.

Designed and maintained Power BI dashboards with optimized data models and DAX measures used by business stakeholders for decision-making.

Partnered with cross-functional teams to define KPIs, improve data quality, and answer real business questions beyond vanity metrics.

Implemented automated refresh schedules and validation checks, reducing manual reporting effort by ~30%.

Used Git and Agile workflows (Jira) to deliver analytics enhancements in a collaborative, production environment.

Leveraged AI-assisted tools (GitHub Copilot, ChatGPT) to accelerate development and troubleshooting.

• Research Assistant, California Lutheran University Aug 2022 – Dec 2023

Built SQL and Python pipelines to extract, clean, and analyze healthcare claims, cost, and utilization datasets for analytics and machine learning use cases.

Applied pandas-based transformations, feature engineering, and validation logic to ensure data accuracy, consistency, and ML-ready datasets.

Supported machine learning and statistical models for trend analysis, forecasting, and outcome prediction on healthcare data.

Created analytical reports and dashboards translating complex healthcare and ML-driven insights into executive- ready outputs.

Improved analytical reliability by ~30% through standardized data validation, documentation, and HIPAA- compliant data handling, including de-identification and controlled access.

• Data Analyst, Konigtronics Pvt Ltd Jun 2020 – Dec 2021

Analyzed 2M+ transactional records to support operational analytics and performance monitoring.

Built SQL and Python pipelines to extract, clean, and analyze large financial and operational datasets.

Applied pandas-based transformations and validation logic to ensure data accuracy and consistency.

Supported forecasting and trend analysis for business planning and operational reviews.

Improved query performance and pipeline reliability through SQL optimization and structured testing.

Collaborated with engineering and business teams to resolve data issues and meet reporting deadlines.

Improved reporting accuracy by 20%+ through reconciliation and validation logic.

• Data Analyst, ICICI BANK LTD Aug 2019 – May 2020

Analyzed customer transaction and lending datasets to support portfolio optimization and decision analytics.

Applied data aggregation and statistical techniques to identify customer behavior patterns and cross-sell opportunities.

Automated compliance and KPI reporting using SQL, Excel, and Tableau for executive decision support.

Delivered insights through clear visualization and storytelling for both technical and non-technical stakeholders. PROJECT

• Financial Risk Forecasting & Customer Behaviour Modelling Feb 2024 – May 2024

Developed machine learning models to predict default risk using large transactional datasets.

Applied statistical analysis and hypothesis testing to validate risk drivers and business assumptions.

Performed model evaluation using ROC, AUC, precision-recall, and confusion matrix to assess risk discrimination and stability.

Conducted model validation and communicated insights through clear visual storytelling. EDUCATION

M.S., Information Technology- California Lutheran University Feb 2022 - May 2024

B.E., Computer Science- Visvesvaraya Technological University Aug 2015 - Jun 2019 LICENSES & CERTIFICATIONS

Power BI Essential Training — LinkedIn Learning

Getting Started with Power BI — LinkedIn Learning

Big Data Analytics with Hadoop & Apache Spark — CPE Capital

Python Data Structures & Algorithms — LinkedIn Learning

Tableau Essential Training — LinkedIn Learning

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