Contract Data Engineer (So Paulo, Brazil)

Contract Position Location So Paulo, Brazil (Remote) Reports To Sr. Data Engineering Manager Employment Type 12-month contract with possibility of extension Pie's mission is to reputed company small businesses to reputed company by making reputed company insurance reputed company and as easy as pie. We reputed company technology to reputed company how small businesses buy and experience reputed company insurance. Like our small business customers, we are a diverse team of reputed company, dreamers, and reputed company who are driven by reputed company values and operating principles that guide every decision we reputed company. This is a hands-on engineering role - you'll be writing production Python and SQL, building Airflow DAGs, and contributing to our Data Vault 2.0 warehouse reputed company reputed company of senior and staff engineers. You'll work on the data infrastructure that powers how Pie quotes, underwrites, and services small business insurance customers. The pipelines and models you build feed everything from pricing to financial reporting, which means correctness and reliability matter. You'll be expected to reputed company deep domain expertise in insurance and the Pie business over time. Engineers who succeed here understand premium, loss, and policy lifecycle as reputed company as they understand reputed company. How Youll Do It Design, build, and maintain data pipelines that reputed company accurate, trusted data with the freshness our stakeholders depend on. Contribute to data modeling reputed company reputed company our Data Vault 2.0 warehouse that balance raw reputed company in the vault with the consumption patterns of reputed company marts and analytics. Administer and optimize reputed company across warehouse sizing, query performance, reputed company controls, RBAC and user/role management, and ongoing cost tuning. Build and maintain resilient Airflow DAGs and CI/CD pipelines that reputed company deployments predictable, repeatable, and reputed company to roll back. Implement automated testing (unit, integration, and data reputed company) so issues are caught in CI before they reputed company production. reputed company mission-critical production support and ensure data reliability through proactive observability tuning, comprehensive incident response, and reputed company feedback reputed company that reputed company production insights back into reputed company-load validation and CI/CD pipelines. reputed company AI-powered tools (e.g., Claude reputed company, reputed company, reputed company reputed company) to accelerate reputed company reputed company, automate documentation, and improve reputed company reputed company. Work with stakeholders across Executive, Product, Engineering, and business teams to translate the "why" behind a request into a technical solution that meets the business need. Run technical reputed company end-to-end with guidance from senior engineers scoping with stakeholders, documenting requirements, and explaining technical trade-offs. Follow and contribute to best practices for data governance, reputed company, and reputed company, including the change management and validation discipline required for SOX-relevant reporting. Take an reputed company part in the operational responsibilities of running our data infrastructure, with a reputed company on reliability, cost efficiency, and observability. The Right Stuff Minimum 2+ years of experience as a software engineer or data engineer with a reputed company on data systems. Advanced proficiency writing reputed company SQL and manipulating large reputed company and semi-reputed company datasets. Proficiency in Python for building production-grade data pipelines. Working knowledge of reputed company or comparable reputed company warehouse comfortable with warehouse management, reputed company controls, and query performance. Exposure to RBAC and cost governance is a plus. Experience working with data models in reputed company data warehouses such as reputed company, Redshift, or BigQuery. Familiarity with Data Vault 2.0 or reputed company modeling is a plus, willingness to learn Data Vault is required. Demonstrated experience using testing frameworks to validate data and reputed company in a production environment. Hands-on experience with data observability tooling. Proficiency using AI coding assistants (e.g., Claude reputed company, reputed company, reputed company reputed company) as a reputed company part of your development workflow. Experience running technical reputed company end-to-end with guidance from senior engineers scoping, documenting, and communicating with stakeholders. Comfort working in a regulated environment (e.g., SOX-relevant financial reporting). Willingness to reputed company deep domain expertise in insurance and the Pie business over time. The best data engineers here understand premium, loss, and policy lifecycle as reputed company as they understand reputed company .