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Data Analyst with less than a year in Data Analysis & ETL Pipeline Development
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Analyst with a B.Tech in Artificial Intelligence & Data Science, experienced in data analysis, ETL pipeline development, data modelling, and business intelligence dashboard creation. Proficient in SQL, Python, Power BI, and modern data stack tools including dbt, Airflow, and Snowflake. Passionate about transforming raw data into actionable insights that drive business decision-making.
Vivekananda Education Society's Institute of Technology
B.Tech · Artificial Intelligence & Data Science
August 1, 2022 – June 30, 2026
TPAC Packaging
Data Analyst Intern
June 1, 2025 – August 1, 2025
Mumbai, Maharashtra, India
End-to-End Sales Business Intelligence Pipeline
January 1, 2024 – June 1, 2026
Built an automated data pipeline that ingests raw sales data from multiple sources, cleans it using Python, and loads it into a Snowflake data warehouse with a structured data model. Wrote dbt models to compute business metrics such as monthly revenue, regional sales performance, and top products, with tested and version-controlled transformations. Scheduled daily pipeline runs using Apache Airflow and connected a live Power BI dashboard for stakeholder reporting.
Customer Segmentation & Retention Analytics
January 1, 2024 – June 1, 2026
Performed RFM analysis using SQL to segment customers into high-value, at-risk, and dormant groups based on purchase behaviour. Conducted cohort retention analysis to understand how different customer groups behave over time and identify drop-off points in the customer journey. Applied K-Means clustering to create customer personas and built a Power BI dashboard showing segment-wise revenue and churn risk.
HR Workforce Intelligence & Attrition Analytics
January 1, 2024 – June 1, 2026
Analyzed employee data to identify attrition patterns across departments, tenure ranges, salary bands, and performance ratings using SQL and Python. Performed salary benchmarking to understand how compensation levels relate to attrition across different experience groups. Built a Power BI dashboard with department-level drill-through, giving HR teams a clear view of headcount, attrition trends, and leave patterns.
AWS Academy Graduate
Amazon Web Services
June 1, 2026 – Present
Rapid Application Development with Large Language Models (LLMs)
NVIDIA
June 1, 2026 – Present
Introduction to Large Language Models
June 1, 2026 – Present
Introduction to Generative AI
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse personal projects (Sales BI, Customer Segmentation, HR Analytics) demonstrate initiative and a broad interest in applying data analysis across different business domains. This indicates adaptability and a proactive learning attitude, which are positive indicators for cultural fit. The certifications in AWS and LLMs also show a commitment to continuous learning and staying current with industry trends. The target role of Data Analyst aligns well with the candidate's demonstrated skills and project experience.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on structured problems, manage data workflows, and present insights, which are crucial for operational fit. The internship experience, though brief, shows exposure to real-world data reporting and supporting decision-making. However, without specific assessment data, soft skills like teamwork, problem-solving under pressure, and communication clarity cannot be fully evaluated.