Data Engineer, CX

Role Overview

As a Data Engineer (CX) at Whatnot, you’ll build and scale data systems that enable data-driven decisions across the company. You’ll partner with stakeholders in Product, Customer Experience, Logistics, Finance, and Trust to design reliable data architectures, ship resilient pipelines, and deliver foundational data products.

Responsibilities

• Own data architecture end-to-end: define how critical business data is captured, modeled, and served.
• Make architectural decisions across storage formats, compute patterns, and SLAs balancing cost, scalability, and consistency.
• Lead CX and Logistics data domains as the data owner, including stewardship of key metrics/concepts such as:
  • Refunds
  • Customer satisfaction and sentiment
  • Shipping
  • Margin
• Design and implement canonical/domain data models as a source of truth for:
  • Analytics, ML, LLMs, and real-time applications
• Establish and enforce modeling standards, ownership boundaries, and data contracts across teams.
• Enforce data quality at scale using:
  • Tests, lineage, monitoring, and reconciliation so anomalies are actionable.
• Automate operational workflows and reduce manual data handoffs by reconciling data across services, warehouses, and external systems.
• Support insights and experimentation by exposing low-latency data via semantic layers, APIs, and real-time query systems.
• Stand up platforms enabling novel experimentation approaches.

Requirements

• 5+ years experience as a data or software engineer building:
  • data warehouses
  • distributed data systems
  • event-driven architectures
• Ability to design/implement data models using dimensional, Data Vault, or ledger-style approaches that support analytical and transactional workloads.
• Hands-on expertise across modern data tooling:
  • Ingestion: Kafka, Debezium
  • Transformation: dbt, Spark, Flink
  • Orchestration: Dagster, Airflow
  • Observability: Monte Carlo, Great Expectations
• Experience operating cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, cost optimization, and workload tuning.
• Comfort writing production-grade Python.

Nice to Haves

• Experience ingesting and operationalizing third-party created data.

Location / Work Style

• Located in San Francisco, CA; team described as remote co-located (hub-based across multiple countries).