Data Engineer, NPI Supply Chain

TekWissen • Sunnyvale, CA

1d • Hybrid

About The Position

Accenture is seeking a Data Engineer to build and own the data foundation for NPI and supply chain AI workstreams. The role involves developing production pipelines, data models, quality controls, and serving layers across product lifecycle management (PLM), manufacturing execution systems (MES), forecast and capacity, and field quality data. The position is a temporary, eight-month hybrid assignment in Sunnyvale, California, with a stated work type of 50% hybrid.

The engineer will implement remediation identified through a dataset assessment, establish continuous data quality monitoring, and create documented pipelines, lineage, and runbooks to support sustainable handover. The role partners with workstream DRIs across product change management, capacity, quality, and EOM to translate process needs into data requirements.

Requirements

• At least 5 years of data engineering experience, including ownership of production pipelines.
• Expert SQL skills and strong Python skills.
• Hands-on experience with Spark or Databricks and a modern orchestration framework such as Airflow or Dagster.
• Experience with dimensional or analytical data modeling on operational or manufacturing data.
• Demonstrated supply chain or manufacturing domain knowledge, including understanding BOMs, forecasts, capacity plans, yield records, or inventory positions.
• Experience integrating enterprise systems through APIs and handling messy, poorly documented source data.
• Experience implementing data quality testing and observability in pipelines.

Nice To Haves

• Prior Meta experience and working knowledge of the client’s data stack, such as Hive/Presto, Dataswarm or equivalent, Databricks, Scuba, and Unidash.
• Direct PLM (Teamcenter) and/or factory MES integration experience.
• Experience preparing data for LLM or agent consumption, including retrieval layers, structured context, or embeddings.
• Hardware NPI or consumer electronics background; Reality Labs exposure.

Responsibilities

• Build and operate production pipelines to ingest, integrate, and model NPI and supply chain data from PLM/Teamcenter, factory MES, forecast and capacity sources, and quality/incident systems.
• Design data models for downstream analytics and AI agents, including conformed dimensions, process-step event models, and reliable joins across program, site, and part.
• Implement the dataset assessment remediation backlog by fixing broken sources, closing latency gaps, and building controls to prevent recurrence.
• Establish automated data quality monitoring and alerting aligned to the referenced seven-dimension framework.
• Build and document APIs, the serving layer, and access patterns consumed by AI workstreams.
• Partner with workstream DRIs across product change management, capacity, quality, and EOM to translate process requirements into data requirements.
• Document pipelines, lineage, and runbooks for sustainable handover.

What This Job Offers

• Career Level: Senior
• Education Level: No Education Listed