Ismael Bovingdon Castillejo

Data Engineering | Cloud | Business Intelligence

Turning raw data
into reliable pipelines

Data Engineer building ETL pipelines with Azure Data Factory, SQL and Python. 4 years of background in high-volume financial systems at BBVA. Currently at Babel & MSc in Data Science (UCM).

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About me

Professional focused on data, cloud and BI

Data Engineer at Babel, where I build end-to-end ETL processes with Azure Data Factory and SQL Server and develop Power BI dashboards for financial and industrial clients while completing an MSc in Data Science (UCM, September 2026).

Before moving into data engineering, I spent 4 years at BBVA Technology developing batch and online financial applications on high-availability critical systems, working with DB2/SQL databases holding millions of records.

Outside work, I design and operate real data infrastructure: a 24/7 ingestion pipeline capturing +320,000 records per day on a Linux VPS, and end-to-end ML pipelines with LLM-based agents. My background in industrial engineering gives me a systems-thinking approach to data architecture.

Technical Stack & Skills

Tools, platforms and key capabilities

Technology · Platforms · Languages

Technical stack

Tools and platforms used in production to build data pipelines, analytical models and robust cloud solutions.

SQL Server Azure Data Factory Databricks Snowflake Power BI Python Apache Spark ETL & Pipelines Gradio LangChain / LangGraph systemd · Linux

Relational databases and high-volume SQL systems
Pipeline orchestration with Azure Data Factory
Executive visualisation with Power BI
Distributed processing with Apache Spark

Capabilities · Business · Methodology

Professional skills

Cross-functional capabilities that translate business needs into functional, scalable, impact-driven data architectures.

Data Engineering Business Analysis Predictive Modelling Reporting & BI Cloud Solutions Process Automation OpenAI API Anthropic API AI Agents Basic MLOps

Design of data-oriented and business-aligned architectures
Automation and monitoring of critical processes
Technical communication with non-technical stakeholders
Problem-solving in high-demand environments

Projects

Professional and personal initiatives

Projects aimed at solving real business problems through data engineering, automation and advanced analytics.

Data Engineering · Real-Time · ML

Madrid Commuter Rail Delay Prediction (RENFE)

24/7 pipeline deployed on a VPS capturing RENFE GTFS-Realtime feeds and AEMET weather data to build from scratch the delay history that RENFE does not publish — the dataset needed to train a predictive model.

Python GTFS-Realtime systemd Linux VPS GitHub / rclone Apache Spark LSTM / GRU

Multi-source ingestion pipeline running 24/7 in production
+320,000 records captured per day
Raw → Parquet → automated Google Drive backup architecture
Resilience verified: automatic restart via systemd after reboot

View architecture GitHub

ML · Generative AI · Interfaces

Pump It Up — Water Pump Prediction (Tanzania)

Full ML pipeline over 59,000 water pumps in Tanzania: from ensemble classification to two production-ready interfaces — a live individual predictor with Gradio and a conversational assistant powered by the Claude API.

Python scikit-learn XGBoost / LightGBM LangGraph Anthropic API Gradio Pandas SHAP Matplotlib

Overall accuracy misleads: the critical class is 7.3%
2× detection rate of repairable pumps vs. base models
Live individual predictor with per-class probability
Conversational AI assistant over the analysis results

View architecture GitHub

Contact

Connect with me

Phone

+34 692 871 279

Email

ishmaelbovingdon@gmail.com

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GitHub

View repository

Location

Remote / Madrid, Spain

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Turning raw datainto reliable pipelines