Cleaning and reconciling messy data from multiple sources, advanced Excel, SQL and Python, and building Power BI dashboards. I check every number against its source, use AI tools daily to work faster while verifying the output, and explain findings clearly to non-technical people.
A data analyst or data engineer role where I can own the full path from messy source data to a trusted report. I enjoy cleaning and reconciling data, building SQL, Python and Power BI solutions, and using AI tools to work faster while checking every output. I’m most interested in product-led startups and consultancies where I can work with real clients and grow quickly, in Sydney or remote.
I’m 23, and I’ve built more real work than most people at my stage: a Master of Data Science finished alongside a part-time data role, two end-to-end pipeline projects with automated tests, and a full-time client-facing job. I learn constantly and fast. I pick up new tools, build with them, and put the proof on GitHub (github.com/MSkandula, maheshsaikandula.com). I’m based in Sydney, open to l work, and can work around US and EU customer hours
In my PAYscope project I built a payments data warehouse with about 75 data quality checks, written twice independently (in SQL and in pandas) so any disagreement exposes a bug. Reconciling the dashboards against the SQL marts caught two reporting errors: counts that were doubled (1,766 vs 883) and an average-of-averages KPI ($130.95 vs $129.61). It taught me to check every number against its source before anyone relies on it.
Technical Support Engineer
Enterprise technology company • Oct 2026 - Present
Junior Data Operations Engineer
Data-focused technology company (part-time casual) • Jun 2025 - Aug 2026
Sydney Transit Intelligence Platform
Data engineering project
PAYscope
Data engineering project
Master of Data Science
Macquarie University, Sydney • 2024 - 2026
Bachelor of Technology in Computer Science and Engineering
GITAM University, India • 2020 - 2024
