Data Engineer - Remote

Role overview

As a Data Engineer at Whatnot, you’ll build and scale the data systems that support data-driven decision-making across the organization, including analytics, machine learning, and real-time applications.

Responsibilities

• Own end-to-end data architecture: define how business-critical data is captured, modeled, and served in production.
• Build and operate data pipelines for both streaming and batch high-volume event data, ensuring low latency, completeness, and accuracy.
• Create domain-oriented data models that act as a single source of truth for analytics, ML, and real-time use cases.
• Enforce data quality and observability via testing, lineage tracking, monitoring, and reconciliation so anomalies are actionable.
• Automate operational workflows by partnering with business systems and platform teams to reduce manual data handoffs and reconcile across services and external systems.

Requirements

• 3+ years experience as a data or software engineer focused on data warehouses, distributed data systems, or event-driven architectures.
• Strong data modeling experience using dimensional modeling, Data Vault, or ledger-style approaches for analytical and transactional workloads.
• Hands-on experience with modern data tooling including: Kafka, Debezium, dbt, Spark, Flink, Dagster, Airflow, Monte Carlo, Great Expectations.
• Experience with cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, workload tuning, and cost optimization.
• Strong Python and SQL skills; ability to integrate into CI/CD and infrastructure-as-code workflows.
• Ability to collaborate across engineering, product, and analytics to translate business requirements into scalable data solutions.
• Self-starter who can own both technical design and operational outcomes in a fast-paced environment.

Nice to have

• Experience building data products that directly support internal growth and external user engagement, including near real-time data use cases.