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Pranjal Vijaysing Patil

@pranjalvijaysingpati

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Data Engineer turning complex data into reliable KPIs, insights, and self-service BI.

India

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What I'm looking for

I’m looking for a role where I can build reliable data pipelines, enforce data quality and governance, and deliver self-service BI. I want to work with teams that value clear KPI definitions and measurable impact in production.

I’m a Data Engineer who builds analytics platforms that make KPIs consistent, trustworthy, and easy to use. At Barclays Bank PLC, I standardized 5,000+ business KPIs into a single dimensional data model, improving report delivery and reducing ad-hoc reporting demand.

I focus on end-to-end data quality and governance—implementing 500+ automated checks on 500TB of customer data with Great Expectations and Airflow, and reducing downstream error tickets dramatically. I also designed metadata-driven GDPR archival workflows to cut manual classification effort while maintaining zero regulatory findings.

I’ve paired engineering with analytics impact by delivering self-service Tableau and Power BI layers and supporting business teams with validated data models. Currently, I’m expanding into deep learning and explainable ML through research on multivariate time-series, using SHAP and MLflow to turn model outputs into actionable decisions.

Experience

Work history, roles, and key accomplishments

Current

Graduate Research Assistant

Current

Georgia State University

Aug 2024 - Present (2 years)

Analyzed multivariate time-series data using Random Forest and gradient-boosted models with walk-forward cross-validation, improving forecast accuracy and reducing false positives. Built an FFT-based spectral feature pipeline and used SHAP and counterfactual analysis to explain predictions, tracking experiments in MLflow and Weights & Biases.

Random Forest Gradient Boosting Time Series Analysis FFT SHAP MLFlow Weights Biases

Data Engineer

Barclays Bank PLC

Sep 2021 - Jun 2024 (2 years 9 months)

Standardized 5,000+ business KPIs into a single dimensional data model and validated definitions with 10+ business units, reducing report delivery from 3 days to 1 day. Rebuilt PySpark ingestion logic for CRM/Pega dispute data and implemented automated data quality checks on 500TB using Great Expectations and Airflow.

SQL PySpark Python Dimensional Models Tableau Power BI Great Expectations Airflow UAT GDPR Metadata Management Data Quality

Business Analyst

Barclays Bank PLC

Jul 2017 - Sep 2021 (4 years 2 months)

Built an Advisor Performance analytics tool tracking 16 operational KPIs in Tableau, reducing the performance review cycle from 4 weeks to 1 week for 1,000+ frontline staff. Designed FCA regulatory reporting dashboards in Power BI backed by validated SQL data models and ran A/B tests to improve advisor-risk identification.

Tableau Power BI SQL A B Testing Regulatory Reporting FCA ETL KPIs Query Optimization

Education

Degrees, certifications, and relevant coursework

Georgia State University

Master of Science, Computer Science

2024 -

Grade: 3.99/4.00

Pursuing an M.S. in Computer Science with coursework in advanced deep learning, data mining, spatial/scientific databases, and generative AI/LLMs (Sep 2024–Aug 2026). GPA: 3.99/4.00.