Ítalo
Guimarães.

Senior Data / AI Engineer — Remote — Brazil

• Design and optimize large-scale Spark/Databricks pipelines for high-volume financial datasets, owning the full SDLC: architecture, implementation, performance tuning, data quality, CI/CD, monitoring, and documentation.
• Maintain Delta Lake tables as the system-of-record for product and risk teams, applying best practices for schema evolution, ACID transactions, and incremental processing patterns (merge, upsert, CDC) with Unity Catalog governance.
• Build AI agent tooling (LangGraph, ReAct, MCP) integrated with internal platform services and data pipelines, designing clear service boundaries, retry/fallback strategies, and observability for production-grade agentic workflows.
• Implement data quality controls, alerting, and lineage tracking to guarantee correctness and reliability for downstream consumers at fintech scale (100M+ users).
• Lead technical design reviews and code reviews, mentoring engineers on Spark performance tuning, data modeling trade-offs, and scalable design patterns.

Data Engineer — Remote — Brazil

• Led DataOps operations for Dasa Medicina Diagnóstica, monitoring data ingestion and optimizing computational resources across the GCP environment (Cloud Composer, BigQuery, GCS, Dataproc).
• Managed Apache Airflow DAGs in Cloud Composer, ensuring efficient execution of critical ETL pipelines and high availability of the data platform.
• Developed and optimized PySpark jobs on Dataproc for large-scale data transformation with dimensional modeling and query optimization in BigQuery.
• Provisioned infrastructure on GKE/Kubernetes with Terraform; implemented monitoring and automated alerting with Grafana, increasing reliability and reducing MTTR on complex pipeline incidents.

Data Engineer — Industrial IoT & Equipment Monitoring — Remote — Brazil

• Built production Python-based data ingestion pipelines for structured and unstructured sensor data generated by industrial equipment monitoring devices (vibration, temperature, current, runtime telemetry).
• Integrated MongoDB as the primary operational source, extracting heterogeneous equipment telemetry and event data and loading it into ClickHouse (optimized for high-frequency time-series queries) and PostgreSQL for operational analytics.
• Orchestrated Python extraction and ingestion scripts for scheduled and event-driven data flows, ensuring reliable, low-latency processing of high-frequency industrial sensor readings in production at scale.

Data Engineer — Remote — Brasília, DF, Brazil

• Architect and maintain a distributed data platform integrating PostgreSQL, DuckDB, and AWS services (S3, Lambda) as a system-of-record for national health indicators, with schema versioning, access governance, and auditability.
• Built the SISVAN pipeline integrating operational data from national food and nutrition surveillance systems into a structured, analytics-ready fact table with completeness tracking and audit capabilities — paper accepted at SEMISH/CSBC 2026.
• Automated CI/CD workflows via GitLab for infrastructure and code artifacts; implemented schema migration tooling and multi-environment deployments.

Data Engineer — Remote — Belo Horizonte, MG, Brazil

• Designed enterprise Data Lakehouse architectures for financial and healthcare clients using AWS (S3, Glue, Redshift, Athena) and GCP (BigQuery, GCS, Dataproc), implementing Star and Snowflake Schema dimensional models.
• Orchestrated ETL pipelines with Apache Airflow and AWS Glue; implemented data catalog (DataHub, OpenMetadata) and quality tooling (Great Expectations, SODA).
• Led code reviews and defined engineering standards (idempotency, testability, documentation); mentored engineers on distributed systems and data modeling best practices across multi-client squads.

Data Engineer — Remote — São José dos Campos, SP, Brazil

• Led the Data Ecosystem initiative: designed raw-to-refined Data Lake zones (raw, trusted, refined) ingesting operational manufacturing data from heterogeneous sources (SQL Server, Oracle, SAP, GCP databases) using PySpark, NiFi, and Airflow across AWS and GCP.
• Built operational data pipelines ingesting sensor and process telemetry from manufacturing systems into cloud analytics infrastructure — directly analogous to OT-to-cloud industrial data integration.
• Built analytical dashboards in Power BI for IT teams (Service, Quality, Delivery, Costs); automated KPIs, spreadsheets, and management systems; administered Power BI capacity.
• Applied DevOps practices for production reliability and monitoring; managed relational and non-relational data across SQL and NoSQL stores.

Software Engineer (Intern) — Brasília, DF, Brazil

• Managed Oracle databases and developed enterprise Oracle APEX applications; optimized relational schemas and query performance for internal government audit systems.

Computer Vision Researcher — Brasília, DF, Brazil

• Developed and researched predictive models for road lane detection using convolutional neural networks and deep learning in the CARLA autonomous driving simulator; applied data mining and analysis techniques.