Data Engineering Specialist

About the role

Join the Data Strategy team at Guy Carpenter, a business of Marsh, to build and operate firm-wide data products and bespoke business applications for a global reinsurance business. This is a customer-facing, product-oriented role focused on turning business problems into reliable, stakeholder-facing outcomes end to end. It is based in Sao Paulo with a hybrid model, and professional fluency in English is required.

Key responsibilities

• Build and maintain ETL/ELT pipelines, ingestion workflows and data models on Databricks using Python and SQL.
• Translate ambiguous business problems into practical data products with clear success criteria.
• Own solutions end to end: design, deployment, monitoring, maintenance and improvement.
• Work with product managers, business stakeholders and technical partners, applying testing, CI/CD, code review, observability, documentation, lineage and alerting.
• Make trade-offs across performance, reliability, cost and latency and communicate them clearly.
• Partner with data scientists and analysts on pipelines supporting analytics and AI/ML use cases, and contribute to shared engineering patterns and tooling.
• Use AI tools pragmatically to improve delivery while validating outputs.

Required profile

• Senior-level data engineering experience (or closely related roles).
• Proven ownership of at least one production data product used by real stakeholders.
• Bachelor's degree in a quantitative field (or equivalent practical experience).
• Professional fluency in English and availability for hybrid work in Sao Paulo.
• Proactive, low-supervision working style and ability to work directly with business stakeholders.

Required skills

• Strong Python and SQL, able to write production-grade code.
• Hands-on experience with Databricks (mandatory).
• Building ETL/ELT pipelines and production data systems, with data quality and integrity checks.
• Preferred: consulting experience, experience in insurance/reinsurance or financial services, Azure Data Factory, dbt, APIs and integrations, MLOps concepts, BI tools such as Power BI, Tableau or Looker.