We love technology, and we enjoy what we do. We are always looking for innovation. We have social awareness and strive to improve it daily. We make things happen. You can trust us. Our Enrouters are always up for a challenge. We ask questions, and we love to learn. We pride ourselves on having great benefits and compensations, a fantastic work environment, flexible schedules, and policies that positively impact the balance of work and life outside of it.

At Enroute, we are looking for a Data Engineer - Data Conversions to join a high-impact engineering team. As a Data Engineer on the Conversions team, this person will play a critical role in migrating insurance policy data from administration systems to a modern policy administration platform. This is an analysis-first role with a data engineering component: the primary work is to deep-dive into data, trace and reconcile information across multiple data layers (databases and files), build the mappings and transformations that move legacy data into the target format, and resolve data quality issues to deliver validated loads.

Strong, hands-on command of SQL as a language is essential, and the role makes heavy, daily use of AI tooling to accelerate that work. The position offers direct mentorship from an experienced conversion manager and exposure to the full data migration lifecycle, from initial discovery through production cutover. It requires technical fluency combined with effective communication to support iterative delivery cycles, and it suits someone adaptable who is eager to learn the team's conversion methodology.

Requirements

Technical:

- Strong, hands-on command of SQL as a language (the core skill for this role) — able to independently write and reason through complex queries to analyze, trace, and transform data.

- Proficiency in SQL Server: queries, views, stored procedures, CTEs, window functions.

- ETL (Extract, Transform, Load) processes.

- Building source-to-target data mappings and transformation logic.

- Data validation and data cleansing practices.

- Cloud database experience — AWS: RDS, S3, Secrets Manager.

- Proficiency in Excel for data analysis and legacy data review.

- GitHub / version control.

- Project management software (e.g., Jira).

- Agile methodologies (e.g., Kanban, Scrum).

- Secure handling of sensitive financial data and personally identifiable information (PII).

- Experience using AI coding assistants (Claude, GitHub Copilot, or similar) for development workflows, prompt engineering, and automated analysis.