As a Principal Data Engineer on the mGPS/Compass team, you will own how indoor positioning data flows across the platform, from events emitted by mobile SDKs and backend services, through streaming and batch pipelines, to analytics and the tools associates and engineers rely on. You will design reliable, cost-efficient, privacy-compliant data systems, write production code, and set the technical direction for the team. You will partner closely with product, positioning vendors, and partner-app teams to turn location data into measurable operational outcomes.
About the team:
The mGPS/Compass team builds the in-store positioning and routing technology that helps associates find items faster and fulfill orders accurately. Our work turns indoor positioning data into meter-level routing and real-time paths, saving millions of associate hours every year. Engineers here work across data systems, services, and cloud-native design in a multi-cloud (Azure and GCP) environment and see the impact of their work in stores quickly. We value ownership, engineering excellence, and continuous improvement.
What you'll do:
- Own the end-to-end data flow of the mGPS/Compass platform, from SDK and service events through streaming and batch pipelines to analytics and the tools our associates and engineers use.
- Lead technical design and architecture, including breaking a large service into well-bounded domain services with a safe, incremental migration.
- Write and review production code across data pipelines, backend services, and lightweight web tools, and set the quality bar for the team.
- Partner with product, vendors, and partner-app teams to turn indoor positioning data into measurable operational outcomes.
- Drive reliability, performance, and cost efficiency, with strong observability, privacy compliance, and on-call health.
- Lead platform engineering efforts by delivering scalable infrastructure, reusable tooling, and cloud-native architectures aligned with strategic roadmaps.
- Architect and implement AI-enhanced applications and intelligent systems supporting millions of users with real-time data processing capabilities.
- Drive scale and performance work like Kafka partitioning/throughput, API latency, cache strategy, data-pipeline cost (GCP BQ optimizations)
- Partner with product, vendors (positioning technology), and partner-app teams (mobile apps, supplier and associate tools) on SDK contracts, SLAs, rollout plans and incident response.
- Improve operational excellence by enhancing observability, alerting, canary deployments, runbooks, change-management discipline, on-call health.
What you'll bring:
- Data engineering: hands-on experience building production streaming and batch pipelines with Kafka (partitioning, retries and DLQ, idempotency) and BigQuery/SQL, with attention to cost and performance.
- Backend engineering: strong Java (Spring Boot 3.x, Java 17/21), REST API design, and relational data (PostgreSQL), with experience designing distributed, cloud-native services.
- Technical leadership: a record of leading architecture across teams, writing design docs/ADRs, and mentoring engineers at staff level.
- Demonstrated ability to apply model-driven design and leverage AI agents to enhance software solutions.
- Working knowledge of TypeScript, Node.js, and React for internal tools and admin UIs.
- Cloud-native delivery experience: Kubernetes, CI/CD, canary or progressive delivery, secrets management, and observability (metrics, tracing, alerting).
- Experience with Airflow or Spark/Dataproc-style batch workflows.
- A strong testing mindset: unit, integration, and end-to-end tests, plus contract and load testing.
- Design, build, and operate the pipelines that move Compass event data from Kafka into BigQuery and analytics, keeping them reliable, cost-efficient, and privacy-compliant.
- Write and review Java backend and React/TypeScript code for the services and tools that expose that data.
- Work with product, vendors, and partner-app teams on data contracts, rollouts, and incident follow-ups.
- Mentor engineers, lead design reviews, and improve monitoring, alerting, and runbooks.