Senior Data Engineer – Hardware & Supply Chain

This job was selected by the SpringCube team to help AI, Data and Cloud Engineers discover relevant San Francisco Bay Area employers. Sign up to view the full employer details and apply directly with the hiring company.

Company Overview

A rapidly growing consumer technology company develops connected hardware and software products designed to help people better understand their daily health, readiness, activity, and sleep. Its products combine wearable technology, connected applications, and data-driven insights to support healthier lifestyles for a global community.

The Data Engineering & Analytics team builds the data infrastructure that supports hardware operations, analytics, and business decision-making. The team works across manufacturing, quality, supply chain, firmware, and broader data platform initiatives to create reliable and scalable data systems.

The organization is seeking a Senior Data Engineer – Hardware & Supply Chain to build and maintain the data infrastructure supporting hardware manufacturing operations. The role will focus on production yield, device traceability, quality metrics, supply chain data, and the integration of manufacturing systems into a scalable data platform.

The successful candidate will work closely with Hardware Engineering, Operations, Quality, and Supply Chain teams to develop reliable data products and pipelines. The position also provides opportunities to expand into adjacent areas such as quality testing analytics, firmware data, and broader data platform engineering as the organization evolves.

Key Responsibilities

Hardware & Manufacturing Data Engineering

• Design, build, and maintain data pipelines that ingest and process manufacturing data from hardware production processes.
• Develop pipelines supporting device yield, assembly, traceability, and supply chain events.
• Build data models that provide Operations, Hardware, and Supply Chain teams with reliable and timely visibility into production performance and supply health.
• Integrate data from manufacturing execution systems (MES), ERP and supply chain platforms, and factory data sources into the organization’s lakehouse.
• Own end-to-end data quality and reliability for Hardware and Supply Chain data, from factory ingestion through analytics-ready datasets.
• Partner closely with Hardware Engineering, Operations, and Quality teams to understand data requirements and deliver scalable data products.
• Ensure manufacturing data systems meet security, compliance, and data governance requirements.
• Contribute to initiatives that reduce single-point-of-failure risks within hardware data infrastructure.

Cross-Functional Growth Areas

• Expand data engineering support into Quality Testing and firmware data domains.
• Contribute to broader lakehouse architecture using Apache Iceberg, Databricks, and dbt.
• Support Data Mesh initiatives by establishing Hardware and Supply Chain as an owned data domain.
• Contribute to broader platform engineering initiatives as the data organization evolves.

Required Qualifications

• 5+ years of experience in data engineering, with exposure to manufacturing, operations, or supply chain data.
• Strong SQL and Python skills with a demonstrated ability to build reliable production data pipelines.
• Experience integrating data from manufacturing systems such as MES, ERP platforms, factory IoT systems, or supply chain platforms.
• Ability to model manufacturing data, including production lots, device traceability, yield events, and supply chain transactions.
• Experience operating production data systems on AWS or an equivalent cloud platform.
• Strong understanding of data pipeline reliability, quality, and scalability.
• Ability to work independently and manage responsibilities effectively within a distributed team.
• Strong communication and collaboration skills, particularly when working with Hardware and Operations stakeholders who may not have a data engineering background.
• Self-motivated and pragmatic approach to solving complex data engineering challenges.

Preferred Qualifications

• Hands-on experience working with hardware manufacturing data within a consumer electronics or IoT company.
• Experience with device traceability, serialized manufacturing, or supply chain event modeling.
• Familiarity with Databricks, Apache Iceberg, or dbt.
• Exposure to Quality Testing data systems.
• Experience working with firmware or device telemetry data.
• Experience contributing to lakehouse architecture or Data Mesh initiatives.

Disclaimer

SpringCube curates tech job listings from various company websites to support tech professionals globally.

1.No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.

2.No Client Relationship: This company is not a client of SpringCube unless stated.

3.To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job.

4.No Liability: SpringCube is not liable for inaccuracies.**