Own and build the production-grade data layer that powers a Claims AI / Intelligent Suite running on Azure Databricks.
Design, build, and maintain production-grade data pipelines in Azure Databricks using Delta Live Tables and Structured Streaming.
Implement and operate medallion architecture (bronze, silver, gold) with clear data contracts, quality controls, and freshness SLAs.
Build and maintain scalable data models and feature tables for claims, policies, litigation, and adjuster data.
Engineer data preparation pipelines for AI workloads, including structured data serving and unstructured document processing for vector search and RAG use cases.
Enforce data quality, observability, and reliability through automated checks, lineage, schema enforcement, and freshness monitoring.
Own pipeline orchestration, CI/CD, monitoring, and failure recovery for production data systems.
Collaborate closely with AI Engineers and the Lead Databricks Architect to align data architecture with agentic AI and platform decisions.
Work with client data owners and platform teams to manage data access, upstream changes, and source system dependencies.

7+ years of experience in Data Engineering with strong hands-on experience building production pipelines on Databricks (PySpark, Delta Lake, DLT) – Databricks is a must.
Deep knowledge of Delta Lake optimization, streaming and batch patterns, schema evolution, and performance tuning.
Solid experience with Unity Catalog, data governance, and secure data access patterns.
Strong SQL and PySpark skills, with a production engineering mindset.
Experience building CI/CD for data pipelines and operating data systems in production.
Strong Azure fundamentals (ADLS Gen2, identities, Key Vault, security and networking concepts).
Data quality and reliability mindset with experience implementing observability and quality frameworks.
Ability to work independently and take ownership after high-level direction is provided (“run with the ball”).
Experience with Insurance (P&C / Commercial Liability) and AI/ML data platform experience is a strong plus.
Databricks Data Engineer Professional or Azure Data Engineer Associate certification is a plus.
You will need excellent written and verbal English for clear and effective communication with the team.

Learning Opportunities: Certifications in AWS (we are AWS Partners), Databricks, and Snowflake. Access to AI learning paths to stay up to date with the latest technologies. Study plans, courses, and additional certifications tailored to your role. Access to Udemy Business, offering thousands of courses to boost your technical and soft skills. English lessons to support your professional communication.
Travel opportunities to attend industry conferences and meet clients.
Mentoring and Development: Career development plans and mentorship programs to help shape your path.
Celebrations & Support: Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones. Company-provided equipment.
Flexible working options to help you strike the right balance. Other benefits may vary according to your location in LATAM.

Principal Data Engineer

Key skills