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Data Analyst with less than a year in Python, SQL & Power BI
NIT Trichy graduate with hands-on experience building Python ETL pipelines, writing advanced SQL, and delivering Power BI dashboards that business teams actually use. At Orinson Technologies, cut weekly reporting time by 40% and eliminated 60% of manual validation work across five data sources. Also ran analytics independently for a wholesale distribution business — 10,000+ transactions cleaned and analyzed, overstock reduced by roughly 20% through seasonal demand tracking. Covers the full data flow: raw ingestion and cleaning, SQL transformation, cloud ETL on Azure, and final BI delivery. Looking for analyst or BI roles where the output connects directly to business decisions.
National Institute of Technology, Tiruchirappalli (NIT Trichy)
B.Tech · Civil Engineering
August 1, 2022 – June 30, 2026
Orinson Technologies
Data Analytics Intern
June 1, 2024 – August 31, 2024
India
Pharma Data Insight Automation
June 20, 2026 – Present
• Built an automated ingestion pipeline to pull pharmaceutical sales reports from 10+ regional Excel files, standardize inconsistent schemas, handle missing values, and load clean data into SQL—eliminated 3+ hours of weekly manual consolidation. • Developed a multi-page Power BI dashboard with drill-throughs covering regional drug performance, YoY growth trends, stockout risk indicators, and top-SKU revenue—gave distribution teams data to drive procurement decisions. • Parameterized SQL queries for dynamic filtering by region, time period, and drug category; connected to Power BI via DirectQuery for on-demand ad hoc reporting. Pipeline reduced manual reporting effort by ~70%.
Sales Data Pipeline & Analytics Dashboard (Cloud)
June 20, 2026 – Present
• Architected a fully cloud-based ETL pipeline: raw CSV data uploaded to Azure Blob Storage, transformed via Azure Data Factory (linked services, datasets, copy activities), and loaded into Azure SQL Database. • Configured incremental load logic in ADF using watermark columns—only new or updated records processed per run, keeping pipeline compute costs minimal. • Built a multi-page Power BI dashboard covering regional revenue, product category trends, MoM sales velocity, and KPI scorecards. Demonstrates cloud data engineering end to end: ingestion → transformation → storage → BI visualization.
Cultural Fit Analysis
The candidate's diverse project portfolio, including both personal and internship experiences, shows a proactive and self-driven approach to learning and applying data analytics skills. Their involvement in leadership roles during college indicates a collaborative spirit and ability to work in teams. The stated interest in roles where output connects directly to business decisions suggests a results-oriented mindset, which is a good cultural fit for many data-driven organizations. The breadth of skills across Python, SQL, Power BI, and Azure demonstrates adaptability and a willingness to learn new technologies.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through their project work, particularly in automating manual processes and standardizing data. Their experience in defining KPIs and working with business teams indicates good communication and stakeholder management potential. The leadership roles in extracurriculars suggest initiative and organizational capabilities. The focus on delivering business value aligns well with operational needs.