Senior Data Platform Engineer

About the Company

Treverse is a fast-growing reverse-logistics company building the operational systems behind reverse logistics inventory tracking systems, pickup workflows, billing, reporting, and AI-enabled decision support.

About the Role

We are looking for a senior engineer to own the data platform and operational data movement that keeps those systems reliable as the business scales. This role is not a dashboard-only analytics role or a pure machine-learning research role. It is a production engineering role for someone who can make data pipelines, backend services, and business-critical integrations reliable, observable, and scalable.

Responsibilities

• Own Airbyte reliability, connector health, sync monitoring, retries, failure recovery, and schema drift handling.
• Own Databricks data availability, pipeline health, data quality checks, and trusted organization-facing datasets.
• Build and maintain backend services that support operational data movement.
• Improve near real-time data flow for pickup, billing, customer, and future bidding workflows.
• Add alerts, runbooks, data freshness checks, and reconciliation so failures are visible before business users are impacted.
• Help make customer-retention data usable, including bidding, winning, pickup, refund, category interest, app activity, and engagement signals where available.
• Support AI and algorithm work by making data cleaner, more available, better documented, and easier to productionize.
• Take ownership of inherited systems and make them more reliable without stopping business momentum.

Qualifications

Must have:

• Senior-level software engineering judgment and ownership.
• Strong backend engineering capability.
• Production experience with data pipelines, data integrations, or operational data systems.
• Ability to debug production issues under pressure.
• Comfort working in ambiguous, fast-moving environments with many priorities.
• Ability to communicate clearly with both technical and business stakeholders.
• Strong learning mindset. Exact tool experience is less important than ownership, adaptability, and sound engineering judgment.

Strong pluses:

• Airbyte, Databricks, AWS, dbt, Kafka or event-driven systems.
• Experience with payment, accounting, ERP, or operational workflow integrations.
• Experience with data observability, freshness SLAs, schema drift, retries, reconciliation, and data quality checks.
• Experience supporting AI, ML, personalization, recommendation, or retention systems from the data platform side.

Example First Projects

• Make Airbyte and Databricks failures visible through alerts, runbooks, and ownership.
• Establish freshness and quality checks for critical operational flows.
• Reduce Chris as the primary incident responder for data pipeline failures.
• Improve data availability for AI and algorithm work and operational visibility.
• Help define the customer-retention event foundation for future analysis and product experiments.

Location and Work Style

This is an on-site role in La Vergne, Tennessee. The company strongly prefers the engineering team to work on site because the systems are tightly connected to warehouse, pickup, billing, inventory, customer, and operations workflows. The right person is comfortable being close to the business, asking questions, understanding operational impact, and building systems that work in the real world.

Pay

Expected range: USD 130,000 to USD 150,000 depending on experience and fit.