Note: The job is a remote job and is open to candidates in USA. Phoenix Ecommerce Technologies is an Autonomous Commerce Platform for DTC Founders, focusing on unifying storefronts and operations through AI. They are hiring a Staff Data Platform Engineer to design and own the data foundation for their agentic commerce platform, transforming raw commerce events into structured intelligence that powers AI-driven decision-making.
Responsibilities
- Design and own canonical data models across transactions, subscriptions, customers, payment attempts, and merchant behavior
- Build event-driven pipelines that transform operational data into structured, replayable intelligence layers with strong guarantees around validation, ordering, idempotency, and observability
- Design low-latency data layers and clear data contracts that power autonomous routing, approval scoring, and checkout optimization
- Create outcome-tracking and feedback pipelines that allow systems to learn from every transaction
- Enable experimentation, measurement, and continuous optimization across merchants while preserving data isolation and platform integrity
- Develop feature-ready datasets and behavioral schemas that support predictive systems such as routing optimization and churn risk
- Lay the groundwork for feature stores and safe model iteration without disrupting live decision infrastructure
- Set the technical direction for how Phoenix models, measures, and activates commerce intelligence
- Collaborate cross-functionally with checkout, payments, and AI teams to translate business problems into structured signals that measurably improve approval rates, conversion, retention, and merchant growth
Skills
- 10+ years of professional experience in software and data engineering, working with production systems
- Hands-on experience using AI coding agents in your daily development workflow
- Strong experience building event-driven architectures and distributed data pipelines
- Deep experience modeling transactional and behavioral datasets
- Understanding of data requirements for agentic and autonomous systems - including grounding, feature readiness, decision traceability, and feedback loop design
- Strong SQL and experience with distributed/cloud-native systems (AWS or GCP)
- Experience working with analytics databases (ClickHouse)
- Experience designing systems that require replayability, correctness, and observability
- Comfort working within a TypeScript/Node.js backend ecosystem
- Startup mindset: comfortable owning ambiguous, high-impact domains
- Experience with event streaming platforms (Kafka, Pub/Sub, etc.)
- Experience preparing datasets for ML models or working with feature stores
- Familiarity with RAG systems or AI retrieval architectures
- Exposure to ecommerce, payments, or subscription platforms
Company Overview