Data Engineer, Payments — Build Global Data Pipelines (Remote)

Whatnot; Seattle (WA); Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Health Insurance

Work From Home Support

Home office setup allowance

Cell phone & Internet allowance

Wellness allowance

Parental Leave

Job summary

Whatnot is seeking a Data Engineer to build scalable data infrastructure powering decisions across the company. You will design data architectures, implement pipelines, and create foundational data products for internal growth.

You will collaborate with payments and finance, analytics, and product engineering, working with Kafka, Debezium, dbt, Spark, Dagster, Airflow, and cloud data warehouses. This role offers remote-friendly hybrid work from multiple US hubs.

Qualifications

• 3+ years of experience as a data or software engineer building data warehouses, distributed data systems, or event-driven architectures.
• Experience modeling data using dimensional, Data Vault, or ledger-style techniques for analytical and transactional workloads.
• Hands-on expertise with data tooling across ingestion (Kafka, Debezium), transformation (dbt, Spark, Flink), orchestration (Dagster, Airflow), and observability (Monte Carlo, Great Expectations).
• Experience with cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, cost optimization, and workload tuning.
• Proficient in Python and SQL, with CI/CD and infrastructure-as-code workflows.
• Ability to collaborate across engineering, product, analytics to translate business requirements into data systems.
• Self-starter in a fast-moving environment, owning both technical design and operational outcomes.

Responsibilities

• Own end-to-end data architecture; decide storage formats, compute patterns, and SLAs balancing cost and scalability.
• Build and operate streaming and batch data pipelines processing high-volume events across domains.
• Design canonical data models to serve analytics, ML, and real-time applications; enforce data contracts.
• Implement data quality systems with tests, lineage, and monitoring to ensure observable datasets.
• Automate workflows and reconcile data across services, warehouses, and external systems.
• Enable insights by exposing high-quality data through semantic layers, APIs, and real-time queries.

Skills

Data Warehousing

Distributed Data Systems

Event-driven Architecture

Data Modeling

Python

SQL

CI/CD

Cross-functional Collaboration

Tools

Kafka

Debezium

dbt

Spark

Flink

Dagster

Airflow

Snowflake

BigQuery

Redshift

Job description

Whatnot is seeking a Data Engineer to build scalable data infrastructure powering decisions across the company. You will design data architectures, implement pipelines, and create foundational data products for internal growth.

You will collaborate with payments and finance, analytics, and product engineering, working with Kafka, Debezium, dbt, Spark, Dagster, Airflow, and cloud data warehouses. This role offers remote-friendly hybrid work from multiple US hubs.