Software Engineer, Data Ingestion

Revolution Parts is a mission-driven organization and pioneer in industry cloud, disrupting and innovating in the automotive space by creating the most active parts network in North America. Since our inception, dealerships have sold more than $1 BILLION in parts and accessories online using the Revolution Parts platform. We are here to transform the way parts buyers and sellers connect.

At the heart of Revolution Parts are our core values:
Think Big, Own It, Wow Them, Leave Your Ego at the Door, Work Together Win Together, and Move Fast, Fail Fast.

Join us in transforming the automotive industry, committed to making a positive impact on our customers and their digital transformation journey.

Revolution Parts is growing rapidly, and the reliability and quality of our core data—catalog, pricing, and inventory—is paramount to our success. This data flows through our established, high-volume ETL pipeline, which is the heart of our platform.

As a Staff Software Engineer, Data Ingestion, you will serve as the technical authority for our data ingestion and persistence ecosystem. You are a "force multiplier," balancing deep hands‑on execution with high‑level architectural strategy. You will own the reliability of our mission‑critical, high‑volume ETL pipelines (PHP, MySQL, Postgre

SQL) while simultaneously defining the 2–3 year roadmap for our next‑generation data architecture.

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor employment‑based visas at this time.

• Preference will be given to candidates who live in the greater Phoenix, Arizona, area.
• This role will require working in our Tempe, AZ (HQ) twice a week.

At Revolution Parts, we expect team members to actively use modern tools—including AI‑powered systems—to improve decision‑making, productivity, and quality of work.

• Using AI tools responsibly to accelerate research, analysis, documentation, and problem‑solving
• Exercising strong judgment around data privacy, accuracy, and ethical use
• Continuously learning and adapting as AI capabilities evolve

Proven examples of using AI to improve outcomes in prior roles is expected.

• Cross‑Functional Liaison and Project Management:
  Act as the primary technical partner for Product, BI, Platform Engineering, and Executive Leadership, translating complex data trade‑offs into business strategy. Own the end‑to‑end lifecycle of complex, multi‑quarter initiatives—from technical discovery to execution. You will utilize Agile, Scrum, or Kanban to manage dependencies across teams, ensuring high‑velocity delivery without compromising architectural integrity.
• Technical
  
  Roadmap:
  
  Define, govern, and drive the long‑term evolution of the data ingestion stack. You will lead the strategic transition toward a V2 architecture (e.g., event‑based processing, modern languages/services) while ensuring the current PHP‑based pipeline remains performant and stable.
• Architectural Governance:
  Establish and enforce engineering standards and data hygiene practices (e.g., schema design, query optimization, observability) across all teams interacting with core persistence tiers.
• Complex Problem Resolution:
  Lead the investigation of the most ambiguous, high‑severity issues regarding data quality, latency, or performance that span multiple microservices and databases.

• Expert System Ownership:
  Become the ultimate authority on our custom ETL workflows for catalog, pricing, and inventory data, taking accountability for its architecture and day‑to‑day performance.
• Data Reliability Champion:
  Design and implement sophisticated monitoring, alerting, and validation frameworks that ensure data accuracy and timely delivery across the organization.
• Pragmatic Debt Management:
  Own the final technical decisions for the ingestion domain, striking the critical balance between immediate stability, feature delivery, and long‑term technical debt.
• Mentorship:
  Act as a formal coach for Senior Engineers, leveling up the organization’s skills in high‑volume…