Whatnot

9 months ago

Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Build and scale the data systems that power data-driven decisions across the company. Own end-to-end data architecture, design canonical domain models, and ship resilient streaming and batch pipelines with strong latency, completeness, and accuracy guarantees. Enforce data quality using tests, lineage, monitoring, and reconciliation. Partner with product, analytics, ML, and platform teams to automate workflows and expose low-latency data via semantic layers, APIs, and real-time query systems.

Location: San Francisco, New York, Los Angeles, Seattle

Workplace: Remote

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Mid level

Key Responsibilities

•Own data architecture end-to-end, including capture, modeling, and serving critical business data, with decisions on storage formats, compute patterns, and SLAs.
•Build and operate streaming and batch pipelines processing high-volume events across user activity, transactions, experimentation, marketing performance, and telemetry.
•Create and enforce canonical domain data models and data contracts across teams to define the source of truth.
•Ensure data quality at scale using tests, lineage, monitoring, and reconciliation so anomalies are actionable.
•Automate operational workflows and enable insights and experimentation by exposing low-latency data via semantic layers, APIs, and real-time query systems.

Pay and Benefits

Salary: USD 180,000 - 260,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVisionHome Office401kPensionParental LeaveChildcareWellness Stipend

Key Requirements

•Have 3+ years of experience as a data or software engineer building data warehouses, distributed data systems, or event-driven architectures.
•Design and implement data models using dimensional, Data Vault, or ledger-style techniques for analytical and transactional workloads.
•Have hands-on expertise with ingestion (Kafka, Debezium), transformation (dbt, Spark, Flink), orchestration (Dagster, Airflow), and observability (Monte Carlo, Great Expectations).
•Operate cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, cost optimization, and workload tuning.
•Write production-grade code in Python or SQL and integrate with CI/CD and infrastructure-as-code workflows.

Experience:Data engineeringStreaming data

Skills:Self-starterCuriosityBias toward actionOutcome-focusedCross-functional partnering

Tech Stack:KafkaDebeziumDbtSparkFlinkDagsterAirflowMonte CarloGreat ExpectationsSnowflakeBigQueryRedshiftPythonSQLCI/CDInfrastructure-as-code

Company Brief

Whatnot

Whatnot is a live-stream shopping marketplace connecting sellers and collectors for trading cards, toys, and collectibles. The platform hosts live auctions and interactive streams, enabling creators and small businesses to sell directly to engaged communities.

Industry: Online Marketplaces

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: United States

Founded: 2019

Website LinkedIn

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Whatnot

9 months ago

Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: San Francisco, New York, Los Angeles, Seattle

Workplace: Remote

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Mid level

Key Responsibilities

•Own data architecture end-to-end, including capture, modeling, and serving critical business data, with decisions on storage formats, compute patterns, and SLAs.
•Build and operate streaming and batch pipelines processing high-volume events across user activity, transactions, experimentation, marketing performance, and telemetry.
•Create and enforce canonical domain data models and data contracts across teams to define the source of truth.
•Ensure data quality at scale using tests, lineage, monitoring, and reconciliation so anomalies are actionable.
•Automate operational workflows and enable insights and experimentation by exposing low-latency data via semantic layers, APIs, and real-time query systems.

Pay and Benefits

Salary: USD 180,000 - 260,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVisionHome Office401kPensionParental LeaveChildcareWellness Stipend

Key Requirements

•Have 3+ years of experience as a data or software engineer building data warehouses, distributed data systems, or event-driven architectures.
•Design and implement data models using dimensional, Data Vault, or ledger-style techniques for analytical and transactional workloads.
•Have hands-on expertise with ingestion (Kafka, Debezium), transformation (dbt, Spark, Flink), orchestration (Dagster, Airflow), and observability (Monte Carlo, Great Expectations).
•Operate cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, cost optimization, and workload tuning.
•Write production-grade code in Python or SQL and integrate with CI/CD and infrastructure-as-code workflows.

Experience:Data engineeringStreaming data

Skills:Self-starterCuriosityBias toward actionOutcome-focusedCross-functional partnering

Tech Stack:KafkaDebeziumDbtSparkFlinkDagsterAirflowMonte CarloGreat ExpectationsSnowflakeBigQueryRedshiftPythonSQLCI/CDInfrastructure-as-code

Company Brief

Whatnot

Industry: Online Marketplaces

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: United States

Founded: 2019

Website LinkedIn