Srikanth Gundeti

Collected, cleaned and transformed data from multiple sources using Python (Pandas) and SQL to create reliable datasets for analysis.

Wrote SQL queries (joins, aggregations, window functions) to extract, filter and validate structured data from relational databases.

Built interactive dashboards in Power BI and Tableau to visualise KPIs, trends and variances for business and operational stakeholders.

Used Python for exploratory data analysis, creating summary statistics, visualisations (Matplotlib/Seaborn) and basic predictive models.

Developed data pipelines and automated reports using Python scripts, reducing manual reporting effort and improving consistency.

Designed and maintained reporting datasets and data models to support self‑service analytics in Power BI/Tableau.

Created and monitored KPI dashboards (e.g. revenue, volumes, cost, service levels) and alerted stakeholders to anomalies and emerging trends.

Worked with AWS services (e.g. S3, Glue, Redshift) to ingest, store and process large datasets in cloud environments.

Implemented data quality checks in SQL and Python to identify missing values, duplicates and outliers, improving accuracy of insights.

Translated business questions into analytical tasks and presented clear, actionable insights to non‑technical stakeholders.

Partnered with operations, finance and project teams to understand requirements and turn them into reports, dashboards and ad‑hoc analyses.

Documented data sources, metric definitions, SQL logic and dashboard specifications to support governance and knowledge sharing.

My most relevant education is my Master of Engineering (Professional) from Deakin University in Melbourne, which had a strong focus on project management, analysis and professional practice in complex organisations. I also hold a Bachelor of Engineering from Sreenidhi Institute of Science & Technology in Hyderabad, which gave me a solid grounding in problem‑solving, structured thinking and working with technical information.