Headline

Data Analyst | Business Analyst | BI & Analytics | SQL, Python, Power BI, Tableau

About

Data Analyst with 1.5+ years turning complex, multi-source data into business insights that drive decisions — from executive dashboards to KPI frameworks used in leadership reviews. MS in Computer Science from California State University, Los Angeles, with a focus on the intersection of Data Engineering and Business Intelligence. What I bring to the table: 📊 ETL Automation: Built and maintained scalable pipelines with Python and Airflow at Cal State LA, resolving recurring failures via root-cause diagnosis and cutting reporting latency by 20%. 📈 Business Impact: At Compass Group, automated ingestion workflows and standardized KPI definitions across global financial dashboards — reducing manual data prep time by 30% and eliminating recurring data quality incidents. 🔍 Analytical Depth: Applied statistical analysis and NLP to real-world datasets (IPL auction value modeling, 50k+ Amazon review sentiment analysis), translating raw data into business-ready insights. Technical Stack: SQL (Window Functions, CTEs, Joins) · Python (Pandas, NumPy, Scikit-learn) · AWS (S3, Redshift) · Tableau · Power BI · Airflow Open to Data Analyst / Business Analyst opportunities where I can bridge technical data work with stakeholder decision-making.

Location

Bengaluru

AI stack

claude code

cursor

gemini

github copilot

Work experience

Student Technical Assistant at California State University, Los Angeles, Sep 2024 - May 2025 · 9 mos, Los Angeles, California, United States, ▸ Standardized data access across reporting teams by designing a unified integration layer (internal APIs + batch jobs), resolving data conflicts and establishing a single source of truth for dashboards. ▸ Investigated recurring Airflow pipeline failures using log analysis and root-cause diagnosis — reduced end-to-end reporting latency by 20% and restored consistent on-time data availability for weekly reporting cycles. ▸ Implemented automated data quality checks across pipeline outputs to prevent downstream reporting errors, improving dataset reliability for analyst and stakeholder teams. ▸ Supported delivery of actionable insights to non-technical stakeholders by maintaining data integrity across 4 production ETL pipelines ingesting from multiple sources.

Data Engineering Intern at Compass Group, May 2024 - Aug 2024 · 4 mos, Los Angeles, California, United States, ▸ Redesigned data models and schema structures in collaboration with BI stakeholders, directly improving Weekly Business Review (WBR) dashboard performance and reporting reliability. ▸ Standardized KPI definitions and reporting logic across global financial dashboards, ensuring consistency in business metrics presented at executive-level performance reviews. ▸ Reduced manual data preparation time by 30% by automating ingestion workflows with row-count validation and schema drift detection — eliminating recurring data quality incidents for the BI team. ▸ Cleaned and consolidated 100k+ row datasets from multiple enterprise systems using Python and SQL, freeing analysts from manual reconciliation.

Data Analytics Intern at AlgoAnalytics, Jul 2022 - Mar 2023 · 9 mos, Pune District, Maharashtra, India, ▸ Mapped the complete customer journey for the first time by engineering backend tracking logic to capture previously unrecorded user actions, creating a new behavioural data stream for the analytics team. ▸ Delivered feature usage insights by analysing pre/post data patterns across system changes — gave leadership direct visibility into user engagement trends that shaped product decisions. ▸ Improved daily analyst productivity by restructuring relational tables and adding strategic indexes, reducing query response times for high-frequency reporting queries.

Education

Master's degree, Computer Science, California State University, Los Angeles

B.tech, Computer Engineering, Vishwakarma Institute of Technology

Public links

github: https://github.com/Harsh275110