Rajay Jain — Data Analyst who builds the pipeline from messy spreadsheet to clean dashboard, and the story that makes stakeholders actually use it.
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I'm an aspiring Data Analyst based in Goa, India who believes the hardest part of analytics isn't the query — it's making sure the right person trusts the answer enough to act on it. I spend my time in that gap: cleaning inconsistent data, modelling it so it holds up under scrutiny, and shaping the output into something a non-technical stakeholder can read in under a minute.
My toolkit runs from SQL and Python for the heavy lifting, through Power BI or Tableau for the story, out to AWS, Azure and dbt for pipelines that don't fall over at 2am. I care about data storytelling as much as data engineering — a dashboard nobody opens is a failed project, no matter how clean the schema underneath it is.
Core languages run deep; the tooling around them runs wide.
Selected projects from github.com/RajayJain, with headline numbers pulled straight from each README.
Each stage extracts a new skill, transforms it into practice, and loads it into real work.
Started with spreadsheets and relational queries — learning to ask questions data could actually answer, and to distrust numbers without a clear source.
Moved into Pandas, NumPy and Matplotlib/Seaborn to clean messier datasets, automate repetitive reporting, and explore data before committing to a conclusion.
Learned that a chart is a claim — built dashboards designed to be read correctly in ten seconds by someone who has never seen the underlying table.
Currently deepening AWS, Azure, dbt and Docker — building the ETL infrastructure and warehousing layer that keeps analysis reproducible, not just correct once.
Rigorous coursework, end-to-end processing, and continuous upskilling.
Open to data analyst roles and collaborations. Reach out through any channel below.