Data Engineer
Own data and analytics end-to-end: architect internal systems, build metrics/dashboards, and translate customer and product signals into structured inputs for AI agents.
Data Engineer
Builds and scales internal data platform by designing data models, pipelines, and analytics infrastructure to transform raw product/business data into reliable datasets for company-wide decision-making. Partners with stakeholders across Product, Engineering, Finance, Marketing, and Sales.
180k – 250kSan Francisco, CANew York, NYData EngineeringHybrid
About the role
Responsibilities
- Design and maintain core data models and semantic layers
- Develop and orchestrate batch and streaming data pipelines using technologies such as Apache Beam, Kafka, Airflow, or similar frameworks
- Analyze inference and infrastructure telemetry, including data from OpenTelemetry, Grafana, and other observability tools
- Define and maintain company-wide metrics across product usage, performance, and customer lifecycle
- Enable self-service analytics through agents and tools, with well-structured semantic layers and context
- Ensure data reliability and quality through testing, documentation, and governance
Preferred Qualifications
- Understanding of inference metrics such as latency, throughput, token usage, and model performance
- Experience supporting B2B SaaS and/or consumption-based platforms
- Application of forecasting and predictive modeling (e.g., ARIMA, Prophet) to business processes
Benefits
- Competitive compensation, including meaningful equity
- 100% coverage of medical, dental, and vision insurance for employee and dependents
- Generous PTO policy including company wide Winter Break
- Paid parental leave
- Company-facilitated 401(k)
Skills
Apache BeamKafkaAirflowOpenTelemetryGrafanaData PipelinesSemantic LayersBatch ProcessingStreaming DataData Modeling
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