Headline

Data & Analytics Engineer | Pipelines + dashboards leaders decide with | Python · SQL · Snowflake · dbt · Airflow | Open to work

About

I'm a Data & Analytics Engineer (~5 yrs across Indeed and TCS) who builds the pipelines and the dashboards leaders decide with. I work across the data stack — Python and SQL for ingestion and transformation, Snowflake for warehousing, and Tableau / Power BI reporting that the C-suite actually opens. I'm now extending into the modern orchestration stack (Airflow, dbt, CI/CD) and shipping public projects to prove it — you'll find them on my GitHub and portfolio below. 🟢 Open to: Data Engineer · Analytics Engineer · BI Analyst. Immediate joiner, open to relocation, comfortable across global time zones. Stack: Python · SQL · Snowflake · Tableau · Power BI · Airflow · dbt · Git · CI/CD

Location

Bengaluru

AI stack

claude code

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cursor

replit

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Work experience

Business Intelligence Analyst at Indeed, Nov 2024 - May 2026 · 1 yr 7 mos, Bengaluru, I have successfully contributed to data-driven decision-making at Indeed by enhancing visibility and engagement metrics. • Developed dashboards that significantly improved data visibility for sales teams and product teams. • Built efficient ETL pipelines to streamline data processing for lead generation tools. • Collaborated on A/B testing initiatives to optimize user entry points and monitor subscription revenue health.

Data Analyst at Tata Consultancy Services, Jul 2021 - Nov 2024 · 3 yrs 5 mos, Bengaluru, Karnataka, India, Spearheaded automation of 10+ manual processes with Python Scripts, resulting in a 75% reduction in data analysis time. - Analyzed client behavior by generating sales reports from 40+ geographies and implemented a data warehouse handling 150 GB of data in SQL Server and Excel. - Created a reporting tool in Python (Django) improving efficiency by 94% in tracking website statistics across 20+ branch office locations. Responsibilities: - Automated manual processes using Python scripts - Conducted client behavior analysis based on sales data - Stored, organized, and examined large datasets - Developed reporting tools for efficient data tracking - Produced monthly reports with advanced Excel functions Achievements: - Reduced data analysis time by 75% through process automation - Improved efficiency by 94% in tracking website statistics - Handled 150 GB of data comfortably with a developed data warehouse Tech-stack: Python( Numpy, Pandas, Seaborn, Matplotlib) , SQL Server, Excel, Power BI-

Education

Master of Business Administration - MBA, Finance and marketing, University of Madras

Bachelor of Technology, Rubber and Plastics Technology, Anna University Chennai

Public links

github: https://github.com/vigneshv-analytics