Data Engineer building production batch, lakehouse, and streaming pipelines with Python, SQL, dbt, Spark, Airflow, AWS, and Azure.
AWS Certified Data Engineer - Associate (February 2026) and Azure Databricks Platform Architect.
Open to Data Engineer roles in Madrid or remote.
AWS-native pipeline designed for 10M+ healthcare records per day with GDPR Article 17 compliance.
- Impact: ~65s erasure SLA, 8,500+ records/s ETL throughput
- Stack: AWS Glue, Athena, Redshift Serverless, Lambda, KMS, CloudFormation
Azure lakehouse pipeline implementing Bronze, Silver, and Gold layers with infrastructure provisioned through Terraform.
- Scope: 7M+ orders, 200K customers, 500 products
- Stack: Terraform, Azure Data Factory, Databricks, PySpark, Delta Lake
Production ETL pipeline consolidating academic data from multiple sources into analytics-ready models.
- Impact: runtime reduced from 15 min to ~5 min, production errors down 90%
- Stack: dbt, Airflow, DuckDB, PostgreSQL, Docker, GitHub Actions
Real-time order processing pipeline built around event-driven ingestion and streaming quality checks.
- Stack: Kafka, Spark Structured Streaming, Iceberg, MinIO, Streamlit
- Focus: exactly-once semantics, watermarking, windowed aggregations, anomaly detection
- Batch pipelines and ELT modeling
- Lakehouse and medallion architectures
- Data quality, reliability, and operability
- Cloud data engineering on AWS and Azure
- LinkedIn: linkedin.com/in/tomcrojo
- Email:
tomdata03@protonmail.com