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Gabriel Stan

@gabrielstan

Senior Data Engineer at Bosch who built an enterprise GenAI platform that cut information retrieval time by 45%.

At Bosch, I architected an enterprise Generative AI platform combining large language models, retrieval-augmented generation, and enterprise knowledge sources. It helped employees find contextual information and automate knowledge-intensive workflows, reducing information retrieval time by 45%.

I also developed RAG pipelines and a multi-agent orchestration framework with LangChain, LangGraph, and AWS Bedrock. These systems improved retrieval relevance by 30% and task completion rates by 25%.

Previously, at Syneos Health, I built healthcare data pipelines and cloud data architectures for clinical, patient, and operational datasets. Earlier, I developed financial risk and fraud models at Revolut and predictive analytics at IDS Consulting.

Experience

Work history, roles, and key accomplishments

Senior Data Engineer

Bosch

Sep 2022 - Aug 2026 (3 years 11 months)

Architected and developed an enterprise Generative AI platform integrating LLMs, RAG, and enterprise knowledge sources, reducing information retrieval time by 45%. Designed scalable RAG pipelines and multi-agent orchestration frameworks using LangChain, LangGraph, and AWS Bedrock.

Python Apache Spark SQL AWS Lang Chain LangGraph RAG LLM Vector Databases CI CD Docker Kubernetes

Senior Data Engineer

Syneos Health

Jun 2018 - Feb 2022 (3 years 8 months)

Architected and developed scalable healthcare data pipelines using Python, SQL, and Apache Spark, reducing processing time by 40%. Designed cloud-based data warehouse and lakehouse architectures, improving query performance by 45% and reducing costs by 25%.

Python SQL Apache Spark ETL Data Warehouse Data Lakehouse AWS Data Quality Data Lineage HIPAA

Data Scientist

Revolut

Apr 2016 - Feb 2018 (1 year 10 months)

Developed machine learning models for financial risk assessment and transaction analytics, improving risk prediction accuracy by 22%. Built fraud detection models and automated financial reporting using Python, SQL, and data visualization tools.

Python SQL scikit learn Machine Learning Fraud Detection Anomaly Detection Data Visualization Feature Engineering

Data Analyst

IDS Consulting

Dec 2013 - Dec 2015 (2 years)

Developed predictive analytics models using Python, R, and statistical techniques, improving forecasting accuracy by 20%. Built automated data quality pipelines and interactive dashboards using Power BI and Excel.