• Build and support high performance data solutions • Monitoring and responding to our growing network of tools • Facing and overcoming complex technical challenges

• Define and evolve the data architecture and integrations, with a focus on cloud cost efficiency (FinOps). • Conduct technical analyses of the current environment (Azure), identifying inefficiencies, bottlenecks, and opportunities for optimization. • Lead the strategy to migrate ETL pipelines from Azure Data Factory to GCP, ensuring performance, scalability, and cost reduction. • Work directly on building and evolving data pipelines, supporting the team in technical decisions and implementations. • Perform root cause analysis (RCA) for performance, cost, and availability issues, proposing structural solutions. • Define standards for data ingestion, processing, and consumption, balancing cost, performance, and complexity. • Define the target data architecture focused on cost reduction and cloud resource optimization. • Ensure the correct selection of technologies and approaches (batch vs streaming, relational vs non-relational, caching, etc.). • Lead and provide technical support for migrating ETLs to GCP (e.g., Dataflow, Composer, BigQuery, etc.). • Work hands-on reviewing and optimizing pipelines, queries, and jobs. • Work closely with the engineering team to ensure consistent and sustainable technical execution. • Define and monitor efficiency indicators (cost per pipeline, resource consumption, performance). • Document architectural decisions and build a reusable knowledge base. • Support technical prioritization with Delivery and Product, considering financial and operational impact.

• Desenvolver, manter e evoluir pipelines de dados com foco em eficiência, escalabilidade e otimização de custos em cloud. • Atuar na migração de ETLs do Azure Data Factory para GCP, implementando pipelines modernos e performáticos. • Executar análises técnicas do ambiente atual, identificando gargalos, desperdícios de recursos e oportunidades de melhoria. • Apoiar na implementação de soluções para redução de custo (FinOps), incluindo otimização de jobs, queries e uso de infraestrutura. • Realizar análise de causa raiz (RCA) de falhas, lentidão ou alto consumo de recursos. • Trabalhar em conjunto com Arquitetura para garantir aderência aos padrões definidos. • Construir e manter pipelines de ingestão, transformação e disponibilização de dados. • Implementar fluxos de dados em GCP (Dataflow, BigQuery, Pub/Sub, Composer/Airflow, etc.). • Refatorar pipelines existentes visando melhoria de performance e redução de custo. • Monitorar e otimizar jobs, garantindo eficiência no consumo de recursos. • Atuar na migração de pipelines do Azure Data Factory para GCP, garantindo continuidade operacional. • Implementar boas práticas de versionamento, testes e qualidade de dados. • Apoiar na definição de estratégias de processamento (batch vs streaming, incremental vs full load). • Colaborar com times de backend e arquitetura na integração com APIs e sistemas consumidores.

• You’ll help design, build, and maintain data solutions that power reporting and decision-making across the business. • Building and maintaining data pipelines using Google Cloud Platform (BigQuery, Cloud Functions, Cloud Composer, Cloud Scheduler). • Cleaning, transforming, and organising data from multiple sources (APIs, spreadsheets, internal systems). • Automating ETL / ELT workflows to improve reliability and efficiency. • Writing Python (and some Bash) scripts to support data processing and internal tools. • Building and maintaining dashboards and KPI reports using Looker Studio (and supporting data visualisation needs). • Preparing datasets for simple predictive or forecasting use cases as the team evolves. • This is a hands-on role — you’ll be writing code, fixing issues, improving pipelines, and seeing your work used by real teams.