Senior Data Engineer

Job Title

Senior Data Engineer

Role Summary

Owner of Snowcap's Manufacturing Intelligence platform: design and build the data infrastructure to ingest, process, and deliver high-volume telemetry from cryogenic probers, process tools, and environmental sensors. You will work directly with test engineers, process scientists, and fab leads to deliver production-grade pipelines and analytics used to drive manufacturing decisions.

This is a hands-on engineering role to establish the data architecture from first principles under tight schedules; the platform will support the company's cryogenic test facility and future manufacturing campaigns.

Experience Level

Senior-level. The role expects 8+ years building production-grade data pipelines at scale.

Responsibilities

Primary responsibilities include:

• Architect, implement, and evolve the Manufacturing Intelligence platform end-to-end: telemetry ingestion, ETL, data lake, and analytics delivery.
• Design and build ETL/streaming pipelines connecting cryogenic test systems, 300mm wafer prober, process tools, and environmental sensors to a centralized data store with integrity and lineage guarantees.
• Define data schema, quality standards, and wafer-to-device traceability models that govern manufacturing data across process nodes and campaigns.
• Lead onboarding of new high-volume data sources and custom instrument integrations without degrading pipeline reliability.
• Implement observability and monitoring: alerting, lineage tracking, anomaly detection, and data-quality metrics across the pipeline.
• Collaborate directly with physics, test, and process integration leads to translate requirements into data architecture decisions.
• Establish data engineering standards, tooling, and documentation for the function and future hires.

Requirements

Must-have qualifications and skills; nice-to-have items listed afterward.

• Proven experience building and operating production-grade data pipelines at scale (systems with real production SLAs, not prototypes).
• Deep hands-on experience with large-scale telemetry ingestion across streaming, batch, and real-time patterns; understanding of trade-offs in high-throughput instrumentation or manufacturing environments.
• Strong proficiency in Python and SQL.
• Fluency with at least one large-scale distributed data processing framework (e.g., Spark, Flink, Beam, or equivalent).
• Experience designing for observability and data quality from the start (monitoring, alerting, lineage, anomaly detection).
• Domain experience in semiconductor fab, capital equipment, or test environments where data has physical meaning and errors have material consequences.
• Proven ability to work directly with cross-functional engineering and science teams and to prioritize pragmatic architectural choices.
• Nice to have: hands-on experience with SECS/GEM or other semiconductor equipment telemetry protocols; cloud data platform experience; background in yield analysis or equipment health monitoring; exposure to cryogenic systems or superconducting electronics; open-source contributions or shipped tooling.

Education Requirements

BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or equivalent demonstrated depth through industry work (equivalent practical experience accepted).

About the Company

Company: Snowcap Compute

Headquarters: San Francisco, CA, United States

Snowcap Compute develops commercial superconducting digital computers using Josephson junction–based PCL logic that operate at cryogenic temperatures, aiming for dramatically lower power than CMOS. The company combines expertise in quantum physics, cryogenic engineering, and semiconductor manufacturing to build production superconducting chips.