Lead Data Engineer

Role overview Lead the design and delivery of large-scale data platforms, pipelines, and models, while setting technical direction and developing a team of data engineers. A major focus is planning and executing migrations to an Azure Databricks and dbt environment, with attention to production reliability, data quality, and cloud integration.

Responsibilities - Guide and mentor data engineers, set technical direction, review code, and strengthen engineering practices. - Own architecture, design, and implementation for scalable data platforms, pipelines, and data models. - Lead migration planning and delivery involving Snowflake, SSIS, Azure Databricks, and dbt, making architecture decisions and addressing integration, quality, and observability. - Establish infrastructure-as-code practices with Terraform and promote CI/CD and shared architectural standards. - Troubleshoot platform and pipeline issues and work with data, product, architecture, and business stakeholders. - Support team growth through mentoring, training, and managing performance across different levels.

Requirements - At least 8 years of data engineering experience, including 2–3 years in a lead or staff-level position. - Track record owning system design and leading implementation of large-scale data platforms. - Strong hands-on skills in Snowflake, Azure Databricks, dbt, Python, and advanced SQL. - Experience operating large transformation workloads, including thousands of dbt models and pipelines processing terabytes of data daily. - Deep understanding of data architecture, modeling, distributed data systems, and ETL/ELT approaches. - Extensive experience with Terraform, infrastructure as code, CI/CD, and Git-based version control. - Experience leading cloud-to-cloud migrations; AWS-to-Azure migration experience is preferred. - Insurance or financial services experience, including familiarity with claims, policies, underwriting, or risk. - Strong technical leadership, architectural judgment, communication, and stakeholder management.

Nice to have - Data governance, observability, or data quality frameworks; security and compliance knowledge in regulated financial domains. - Streaming experience with Kafka, Event Hubs, Delta Live Tables, or similar technologies. - Familiarity with lakehouse design, cost and performance optimization, or multi-cloud and hybrid environments.

Benefits and work setup - Remote role open to candidates in Costa Rica, Peru, Colombia, or Bolivia.