tuni56
Rocio Baigorria
About
Top Skills
Experience
Data Engineer
Independent Data Engineer Consultant
Feb 2023 - PresentData Engineer specializing in AWS-based data platforms, event-driven architectures, and cost-efficient analytics infrastructure for SMEs and distributed teams.
Key impact:
• Designed streaming pipelines using Kinesis and AWS Glue Streaming ETL, reducing data freshness from hours to minutes.
• Built centralized S3 data lakes integrating multiple sources through Glue and Athena for unified analytics.
• Reduced pipeline latency through Spark job tuning, optimized partitioning, and columnar storage strategies.
• Implemented event-driven architectures using Java, Spring Boot, and Apache Kafka for real-time data exchange.
• Improved pipeline reliability through monitoring and alerting with CloudWatch, Prometheus, and Grafana.
• Implemented infrastructure as code with Terraform to standardize ingestion layers and deployment workflows.
• Automated analytics pipelines reducing manual reporting effort by ~85%.
• Designed serverless architectures prioritizing low operational cost and maintainability.
Business Analyst
Electromecánica Bomeq SA
Jan 2018 - Jul 2022Business-facing analytical role focused on cost optimization, operational efficiency, and decision support.
Key impact:
Conducted root-cause analysis on operational and maintenance costs, reducing annual budgets by 15–20%.
Designed KPI dashboards for operational decision-making, reducing waste by USD 12K+ per quarter.
Managed the full customer lifecycle for 50+ SME accounts, achieving 95%+ retention.
Worked cross-functionally with engineering, procurement, and finance teams to align technical decisions with profitability.
Education
Universidad Tecnologica Nacional
Industrial Engineer, Engineering
2015 - 2022Projects
Real-Time Event-Driven Data Pipeline
Visit Project open_in_new Jan 2026 - Feb 2026Real-Time Stream Processing
Kafka Streams: Complex event processing with windowing and aggregations
Exactly-Once Semantics: Idempotent producers with transactional guarantees
Schema Evolution: Avro schemas with backward/forward compatibility
Fraud Detection: Real-time anomaly detection using sliding windows
???? Production-Grade Observability
Prometheus Metrics: Custom business and technical metrics
Grafana Dashboards: Real-time visualization and alerting
Circuit Breakers: Resilience4j for fault tolerance
Distributed Tracing: Request correlation across services
⚡ High-Performance Optimizations
Batch Processing: Optimized producer batching (32KB, 10ms linger)
Compression: Snappy compression for 40% bandwidth reduction
Parallel Consumers: Multi-threaded processing with manual acknowledgment
Connection Pooling: Optimized database and Redis connections
????️ Enterprise Security & Reliability
Health Checks: Comprehensive service health monitoring
Graceful Degradation: Circuit breaker patterns with fallbacks
Data Validation: Schema registry enforcement
Audit Logging: Structured logging with correlation IDs
Ecommerce Data Warehouse
Visit Project open_in_new Dec 2025 - PresentA production-grade data warehouse implementation for ecommerce analytics, built on AWS using modern data engineering practices. This project demonstrates end-to-end data pipeline design, from raw ingestion to analytics-ready dimensional models.
Business Value
For C-Level:
Single source of truth for ecommerce metrics (revenue, customer lifetime value, product performance)
Serverless architecture reduces operational overhead and scales automatically with demand
Cost-optimized design with pay-per-query pricing model
Historical tracking enables trend analysis and forecasting
For Technical Teams:
Medallion architecture (Bronze → Silver → Gold) ensures data quality and lineage
Infrastructure as Code enables reproducible deployments across environments
Incremental processing minimizes compute costs and latency
Star schema design optimized for BI tool performance
Licenses & Certifications
Data Streaming Engineer Foundations
Confluent
Issued Nov -0001Language & Tools
AWS: S3, Glue, Lambda, Athena, Redshift, Step Functions.
- Infrastructure as Code: Terraform (the only way to build).
- Streaming & Event-Driven: Apache Kafka, Flink (Stateful Processing).
- Environment Management: LXD (System containers), `uv` (Fast Python management).
- Languages:
Python: Data processing, automation, and Boto3 wizardry.
SQL: Complex queries and database sandboxing.
Currently Exploring
Achievements
Fun Fact
Sorry RabbitMQ, you're great, but my heart (and my offsets) belong to Kafka.
Random Dev Quote
Contributions
Articles
- The Hidden Cost of Distributed SystemsJun 11, 2026
- The Art of Cloud Survival: Designing for Failure on AWSMay 21, 2026
- AI-Powered DLQ Triage with Amazon BedrockMay 11, 2026
- Beyond the CLI: Mastering Lambda Invocation Patterns with TerraformApr 29, 2026
- Your Serverless Data Lake is Lying to You: Add Observability or Lose Data (AWS)Apr 20, 2026
Comments
- Strong breakdown of a topic many developers underestimate.
What stood...May 12, 2026
- Love the decision to use the ticker as the Kafka key. Too many people ...May 03, 2026
- Certifications give you the vocabulary, but production gives you the a...May 03, 2026
- @[Fady-Desoky-Saeed-Abdelaziz] Thanks for the comment, Fady! You’re ...Apr 26, 2026
- @[Tom Smith] That framing makes a lot of sense.
What stands out to me...Mar 27, 2026