[Hiring] Lead Software Engineer @Uberall

Role Description

We’re splitting our Analytics & Reporting group into two focused teams: a Data Engineering team that owns data acquisition and the company-wide data platform, and an App team that owns everything our customers touch, including the data-serving APIs, the Analytics section of the Uberall platform, and the reports that turn location data into decisions.

We’re hiring the lead for the App team. You’ll be a player-coach:

• Manage and grow a team of six engineers (3 backend, 2 frontend, 1 QA).
• Partner daily with two Product Managers, a Designer, and a UX Researcher.
• Stay meaningfully hands-on, spending roughly 20–30% of your time on architecture, code reviews, and code.

You’ll work as a peer to the Lead Data Engineer, with a close, explicit contract between your team’s customer-facing products and the data platform that feeds them. This is a role for someone who has led before and still loves to build.

What you’ll own

• Customer-facing data APIs: the public APIs enterprise customers use to access their data, and the microservices behind them.
• The Analytics product: the Analytics section of the Uberall platform, including its frontend, filtering experience, and the APIs powering custom reports.
• Customer reporting: the QuickSight reports our customers rely on, and the gold-layer datasets that feed them. Your team owns its data models end-to-end, built on the self-serve platform the Data Engineering team provides.
• Production: you build it, you run it. Your team deploys and operates its own services (Kubernetes on AWS), owns its observability and SLOs, and runs its own on-call rotation. You lead the incident process.
• The team: hiring, growth, 1:1s, delivery, and the engineering culture of a newly formed team. With one QA engineer among six, you’ll make quality everyone’s job.

What you’ll do in your first year

• Stand up the App team as a healthy, autonomous unit: clear ownership, sustainable delivery cadence, and strong working relationships with Product, Design, and the Data Engineering team.
• Co-own, from the application side, the in-flight migration of data pipelines out of our monolith and into the Data Engineering stack.
• Drive the modernization of our backend estate: the stack is consolidating on Kotlin, and legacy Groovy and Scala services need a pragmatic path forward.
• Shape the next chapter of Analytics: AI-assisted insights in the product, and exposing your team’s data and APIs for consumption by AI agents through the company’s data gateways.

Qualifications

• 7+ years of software engineering experience, with deep backend expertise on the JVM (Kotlin strongly preferred; our stack: Kotlin, Spring Boot, Postgres).
• 2+ years leading an engineering team with genuine people responsibility (hiring, 1:1s, performance, and delivery) while staying hands-on.
• Experience designing, operating, and evolving microservices in production: Kubernetes, AWS, observability, SLOs, and incident management.
• Strong SQL and analytical data modeling skills.
• Experience with RESTful, service-oriented architectures serving external customers at scale.
• Enough frontend fluency (React, TypeScript) to lead frontend engineers well.
• Experience navigating legacy systems and migrations.
• Professional working English (read, write, speak) and comfort collaborating across a remote, distributed organization.

Nice to have

• Experience with Groovy, Scala, or Python - the languages of our existing services.
• Experience with BI tooling (Amazon QuickSight or similar) and data warehouse platforms (Databricks, Snowflake, Redshift).
• Experience building LLM-powered product features or exposing data/APIs to AI agents.