Ewerton R.

Data Engineer @ IBM

About

I’m a Senior Data Engineer who thrives in large-scale, high-impact environments where reliability, scalability, and data quality really matter. Over the last 12+ years (8+ in Data Engineering, DataOps, and SRE), I’ve built, migrated, and optimized data platforms for enterprise-level companies in banking, retail, and insurance. My passion (and expertise) lies in designing cloud-native, observable, resilient data architectures that don’t just move data — they empower business decisions, reduce costs, and scale with confidence. I specialize in end-to-end pipelines, multicloud (AWS, Azure, GCP), distributed data processing (Spark/Databricks/Dataflow), DevOps/DataOps automation, and reliability engineering (SLIs, SLOs, tracing, incident response). What sets me apart: • I combine Data Engineering + Cloud Architecture + SRE — a rare and powerful mix. • I deliver platforms that are fast, reliable, self-healing, and cost-efficient. • I move quickly: diagnose, design, build, automate, optimize. • I excel in complex environments, cross-functional teams, and high-stakes challenges. What I’m looking for: Opportunities where I can: • modernize or rebuild data platforms • design scalable and cost‑efficient architectures • drive DataOps/SRE excellence • improve observability and reliability practices • lead cloud/data modernization initiatives • contribute to strategic, data-driven decisions

Country

Brazil

City

São Paulo

Industry

Insurance

Skill

Azure Service Fabric, Infraestrutura de nuvem, Infraestrutura como código (IaC), Java, Dados em tempo real, Programação orientada a objetos (POO), Operação de dados, Processamento de dados, Arquitetura de data warehouse, Inglês, Inteligência artificial, Data Build Tool (DBT), Analítica, Trabalho remoto, PyTorch, Microsoft Azure Machine Learning, SQL Azure, Desenvolvimento de software, Programação (computação), Hadoop

Experience

Data Engineer

IBM

2019-6 - 2026-2 · 6 yrs 9 mos

São Paulo, São Paulo, Brasil

Senior Data Engineer leading multicloud architectures (Azure, AWS, GCP) for enterprise-level financial and retail players (Casas Bahia, PagBank, Itaú, Bradesco). Azure Highlights: • Built Lakehouse architectures using Azure Databricks and Delta Lake (Medallion), optimizing data processing with Z-Order and Spark Tuning. • Developed complex Azure Data Factory (ADF) pipelines integrating REST APIs, SQL, and Data Lakes. • Automated infrastructure (IaC) via Terraform and CI/CD pipelines in Azure DevOps. • Advanced observability using Azure Monitor and Log Analytics (KQL) to ensure critical SLAs. Multicloud Highlights: • GCP: Led a major Azure-to-GCP migration using Dataflow and BigQuery, reducing operational costs by 30%. • AWS: Implemented data governance with AWS Lake Formation and processing via Glue and Redshift. Tech Stack: Azure (Databricks, ADF, Synapse, DevOps), AWS (Glue, Redshift, Lake Formation), GCP (BigQuery, Dataflow), Python, PySpark, Terraform, Airflow.

DataOps Engineer

Allianz

2017-7 - 2019-5 · 1 yr 11 mos

São Paulo, São Paulo, Brasil

Focused on DataOps and Big Data to optimize insurance predictive models and claims analysis. Key Achievements: • Distributed Processing: Optimized PySpark jobs on AWS EMR, reducing processing time by 25% through memory and partition tuning. • Azure Integration: Implemented data flows integrating on-premise HDFS with Azure Data Lake, streamlining data access for Data Scientists. • Data Enablement: Created curated datasets for Machine Learning models (Fraud and Churn) in multicloud environments. Tech Stack: Apache Spark, PySpark, Hadoop, AWS S3, Azure Data Lake, Python, Hive, Power BI.

Data Lake & Warehouse Support Engineer

Cognizant

2015-2 - 2017-6 · 2 yrs 5 mos

São Paulo, São Paulo, Brasil

Supported and evolved data ecosystems for global retail and finance clients. Key Achievements: • ETL/ELT Pipelines: Developed ingestion flows via Apache Airflow and Pentaho, loading data into Azure SQL and AWS Redshift. • Modernization: Supported the transition from on-premise legacy systems to Azure Blob Storage, ensuring scalability and storage cost reduction. • BI Integration: Configured data connectors for Power BI, enabling real-time visualization of sales KPIs. Tech Stack: Python, Airflow, Pentaho, Azure SQL, AWS S3, PostgreSQL, MongoDB, Power BI.

SRE

Manpower

2011-3 - 2015-1 · 3 yrs 11 mos

São Paulo, São Paulo, Brasil

Specialist in cloud infrastructure reliability and automation, with a strong focus on Azure and AWS environments. Key Achievements: • Azure Observability: Implemented end-to-end monitoring with Azure Monitor and Application Insights, defining SLIs/SLOs for mission-critical services. • Infrastructure as Code (IaC): Provisioned VNETs, VMs, and Azure SQL using Terraform and ARM Templates. • CI/CD: Automated deployments using Azure DevOps and Jenkins, reducing production failures by 20%. • Resilience: Led Post-mortems and implemented Cloud Disaster Recovery strategies. Tech Stack: Azure (Monitor, App Insights, DevOps), AWS, Terraform, Docker, Jenkins, Shell Script, SQL Server.