Open to opportunities

sachin wakale

@sachinwakale

Message

Data Analyst with Python, SQL, and Power BI expertise delivering accurate, automated insights from large datasets.

India

Message

What I'm looking for

I’m looking for a role where I can build reliable data pipelines, optimize SQL, and create dashboards in Power BI—partnering with teams to ensure 100% data accuracy, automate reporting, and turn analytics into action.

I’m an analytical professional with an MCA and advanced certifications in SQL and Power BI. I focus on delivering 100% data accuracy while managing and transforming large-scale datasets across e-commerce and stock market domains.

In my end-to-end e-commerce project, I built an automated ETL pipeline to extract and ingest multi-platform sales data from Shopify and Meesho, enabling centralized reporting. I cleaned, transformed, and validated large datasets with Python (Pandas) and SQL scripts, and I optimized SQL queries and database structures to boost pipeline performance by 30%.

I also developed a Stock Market Trend & Option Chain Dashboard in Power BI, using Python to clean and transform 10,000+ rows for faster, more reliable analysis. I enjoy automating refresh workflows and connecting live datasources so teams can monitor trends and volatility with minimal manual effort.

Experience

Work history, roles, and key accomplishments

Stock Market Dashboard

Feb 2026 - Mar 2026 (1 month)

Built an interactive Power BI dashboard for Nifty 50 and Bank of Maharashtra with KPI cards, trend lines, and volatility indicators. Cleaned and transformed 10,000+ rows of market data with Pandas and automated live refresh workflows for near real-time trend and volatility tracking.

Power BI DAX Python Pandas Data Cleaning KPIs Data Modeling Volatility

E-commerce Data Pipeline

Oct 2025 - Jan 2026 (3 months)

Engineered an automated ETL pipeline to extract and ingest multi-platform sales data from Shopify and Meesho, enabling centralized, reliable reporting. Cleaned and validated large datasets to ensure 100% data accuracy, and optimized SQL queries/structures to boost pipeline processing performance by 30%.