Data Engineer

Data Engineer – Lehi, Utah, United States;
Remote

The Data Engineering team (DAENGR) is the backbone of Route's data ecosystem. We are responsible for the data infrastructure, quality, standards, frameworks, and architecture that power enterprise data, reporting, and analytics across the entire organization. We solve problems of poor data quality and limited accessibility, simplify reporting for teams outside of data engineering, and monitor the uptime, security, and consistency of the majority of Route's data lifecycle.

This is a rare chance to shape the data destiny of a young, fast‑growing company. As Route moves into the AI era of data infrastructure, you will explore new systems and designs, build tools that change how Route operates day‑to‑day, and help migrate from legacy Snowflake pipelines to a modern Databricks‑first architecture, building out an Enterprise Data Warehouse (EDW) with a normalized 3NF core and laying the groundwork for AI‑ready data systems.

• Build and maintain ELT pipelines that ingest data from systems.
• Co‑own the mapping and migration of source data into the new 3NF EDW, ensuring data integrity, reducing redundancy, and maintaining automated unit and data tests.
• Develop data observability processes and monitoring dashboards to track pipeline health, freshness, and data quality across Databricks.
• Build new data and AI‑powered tooling to improve the productivity of the data engineering team and broaden self‑service data access for Route employees and external partners.
• Help harden the Integration Pipeline by automating deployment of shared staging and production infrastructure for new pipelines and managing dependency updates for dbt and CI templates.
• Support the full migration from Snowflake to Databricks, targeting completion by end of Q22027, including reporting services and ingest/egress jobs.
• Coordinate with engineering, analytics, product, and business teams to define and prioritize data requirements and ensure end‑to‑end data lifecycle coverage for existing and new products.
• Champion data democratization, help establish a company‑wide data retention policy, and expand the foundation for a self‑service Silver layer (EDW) that serves as a single source of truth.

• 5+ years of formal, professional data engineering experience
• 4+ years of SQL, fluency in complex transformations, window functions, query optimization
• 3+ years of Python, data pipeline development, scripting, testing, and package management (Poetry)
• 2+ years of experience with AWS (e.g., S3, RDS, DMS, Dynamo
  
  DB) across data‑related services
• 1+ years of experience using Databricks, our primary development platform for this role
• Experience using Terraform and Go Lang
• Pager Duty / Grafana / Tableau, preferred experience
• Understanding of third normal form (3NF) data modeling and when to apply it
• Knowledge and application of data theory
• Working knowledge of data security practices and least‑privilege access standards
• Experience with data access controls in cloud environments (IAM roles, catalog permissions, etc.)

Route is an Equal Opportunity Employer. We embrace diversity and equal opportunity in a serious way. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our work will be.

We offer to pay 95%‑100% of your health insurance premiums for you and your family, remote or hybrid work arrangements, unlimited PTO, 401k matching, formalized growth opportunities, learning & development, DEI programs & events, and so much more.

Salary for this role: $138,000– $146,000. The cash compensation above includes base salary, and is not reflective of potential commission for employees in eligible roles, or annual bonus targets under Route’s bonus plan for eligible roles. In addition to cash compensation, all Route employees are eligible to participate in Routes equity incentive plan to receive stock options per the terms of the agreement.

Some roles may also be eligible for overtime pay. Individual compensation packages are based on a few different factors unique to each candidate, including their career level, skills, experience, specific geographic location qualifications and other job‑related reasons.