Senior/Staff Software Engineer, Data Platform

Axion•San Francisco, CA

9d•$210,000 - $265,000

About The Position

Axion is seeking an experienced Backend Engineer to build and scale the production data ingestion systems that bring customer data into the Axion platform. This is a senior individual contributor role with direct architectural ownership and product impact. The ideal candidate has strong experience working in early-stage companies, building and scaling complex, data-intensive backend systems. In this role, you would work with customer, service, field, telematics, warranty, and aftermarket data from dozens of enterprise systems, often in incompatible formats and with little structure or connection between sources. Getting data onboarding right is essential because everything downstream depends on the integrity of that data. You’ll work closely with both Engineering and Product leadership to define and improve how manufacturer data is ingested, mapped, validated, and prepared for use across the platform.

Requirements

Minimum 5+ years of backend software engineering experience, with deep, recent, hands-on fluency in Python.
Strong cloud architecture experience—designing, deploying, and operating distributed services in production, with Kubernetes and containerized workloads.
Demonstrated depth with Postgres and relational data modeling, including performance, migrations, and schema design under real production load.
A track record of solving genuine data integration problems: heterogeneous sources, messy real-world inputs, and turning all of it into something reliable that downstream systems can depend on.
A pragmatic, tools-not-platforms approach to the data ecosystem—you pick the right technology for the problem rather than building an identity around a single proprietary stack.
A track record of technical mentorship; you make the engineers around you better without needing formal authority.
A firm believer in a "Data First" philosophy who can make sound decisions in ambiguous, fast-moving situations.
A strong executor in fast-paced environments who can balance shipping MVPs with a commitment to production-grade systems.

Responsibilities

Own technical architecture for our data ingestion system, including ingestion pipelines, schema mapping, validation, transformation, and the orchestration that carries customer data from the source to production-ready dataset.
Build and harden the backend services and cloud infrastructure (Python, Postgres, and Kubernetes) that make onboarding a new manufacturer fast, repeatable, and observable, rather than a bespoke engineering project every time.
Solve integration challenges at the source: enterprise warranty, telematics, ERP, and service systems with inconsistent schemas, unreliable delivery, and no shared vocabulary between them.
Establish rigorous data quality and reliability standards (validation, lineage, monitoring, and alerting) so that pipeline degradation is caught by us before it's noticed by a customer.
Partner across Engineering, Product, and customer-facing teams to shape the technical vision and roadmap for data onboarding workflows.
Raise engineering standards through code review, design docs, and the technical direction others build on.
Mentor engineers on data architecture and system design, unblocking hard problems and sharing context generously.