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Data Analytics Engineer with less than a year in Big Data & Business Intelligence
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 Analytics postgraduate (AIR 58 in CCAT) with hands-on experience in collecting, cleaning, and analyzing structured and unstructured data to generate actionable business insights. Proficient in SQL, Python, Excel, Power BI, and Tableau for dashboard development, reporting, and supporting data-driven decision-making across cross-functional teams.
CDAC ACTS, Pune
Post Graduate Diploma · Big Data Analytics
August 1, 2023 – June 30, 2024
MIT College of Engineering, Pune
Bachelors of Engineering · Information Technology
August 1, 2019 – June 30, 2023
Bharati Vidyapeeth Polytechnic College, Pune
Diploma · Information Technology
August 1, 2016 – June 30, 2019
End to End E-commerce Data Pipeline & Analytics
November 1, 2025 – May 31, 2026
Collected, cleaned, and analyzed structured e-commerce data from the Olist dataset to identify sales trends and logistics patterns. Developed Power BI dashboards tracking key business KPIs – sales performance, logistics metrics, and customer trends – for business stakeholders. Implemented Medallion Architecture (Bronze, Silver, Gold) for scalable data ingestion, transformation, and analytics-ready processing. Processed 100K+ records with incremental loading; maintained data accuracy and documented pipeline workflows.
Residential Property Price Analytics and Modeling
May 1, 2025 – October 31, 2025
Collected, cleaned, and transformed real-world residential data from multiple sources for analytics and predictive modeling. Identified key trends and patterns in property pricing through exploratory data analysis and feature engineering. Applied CTGAN-based synthetic data augmentation with statistical validation to improve data scalability and robustness. Developed regression models achieving R2 = 0.96; created Tableau dashboards to communicate findings to non-technical stakeholders. Tracked experiments using MLflow; deployed solution on AWS EC2 via Streamlit for live business insights.
Timetable Scheduling Using Genetic Algorithm
January 1, 2025 – April 30, 2025
Developed a constraint-based optimization solution using Python for scheduling automation. Modelled complex allocation rules and constraints to improve scheduling efficiency. Achieved approximately 90% accuracy and generated Excel based reports for analysis and usability.
HOMESFORTH - Property Portal
September 1, 2024 – December 31, 2024
Implemented backend data retrieval and dynamic filtering using MySQL with structured relational schemas. Maintained data accuracy and consistency across property listing and search workflows.
Python Data Structures & Algorithms
Udemy
June 1, 2026 – Present
Software Engineering
Accenture Nordics
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a breadth of technical skills relevant to data analytics, including data engineering, machine learning, and business intelligence. The projects are diverse, ranging from e-commerce data pipelines to property price analytics and scheduling optimization, indicating adaptability and a willingness to tackle different types of problems. The target role of 'Data Analytics Engineer' aligns well with the candidate's educational background and project experience. However, the lack of professional experience means cultural fit in a corporate environment is yet to be proven.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems, manage data accuracy, and document workflows, suggesting good problem-solving and organizational skills. The academic projects also show an understanding of stakeholder communication and delivering actionable insights. However, without direct work experience or specific soft skill assessments, it's difficult to fully evaluate operational fit and collaboration skills.