Manufacturing Design Engineer Intern

SkydioHayward, CA
10h$47 - $58

About The Position

Skydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users, from utility inspectors to first responders, soldiers in battlefield scenarios and beyond. About the role: As a Summer 2026 Manufacturing Systems Engineering Intern you’ll focus on the systems, data, and analytics that make production run: building and operating data pipelines, integrating MES and shop-floor data sources, and delivering operator-facing dashboards and analytic products that drive decisions across production, quality, and supply chain. You’ll partner with manufacturing, quality, and software teams to translate shop-floor questions into reliable data products that surface root causes, monitor process health, and enable faster, more predictable production ramp. How you'll make an impact (example projects below): Below are representative projects you may own. Each is an opportunity to turn raw production data into reliable insights that scale to full production. Integrate MES / shop-floor data into a central analytics platform Deliverables: integration plan (sources, schemas, cadence), ETL/ELT pipelines ingesting MES / PLC / test-stand data into Databricks (or equivalent), automated data quality checks, and documented data model. Build near real-time production dashboards for operators and supervisors Deliverables: high-level and station-level dashboards (Looker/Tableau/PowerBI or embedded web dashboards) showing KPIs (OEE, yield, cycle time, WIP, rejects), drill-downs to failed units, and operator-facing views. Include mockups, implementation notes, and a rollout plan. Automate KPI calculations & alerts (OEE, first-pass yield, SPC) Deliverables: production-grade Databricks notebooks or jobs that calculate KPI time-series, SPC charts, automated anomaly detection/alerts, and unit-level traceability to identify defect clusters. Build & validate dashboards for pilot builds and line expansion Deliverables: pilot build dashboards, rollout checklist, performance baselines, and documented validation showing that dashboards accurately reflect pilot outcomes.

Requirements

  • Currently pursuing a degree in Industrial Engineering, Manufacturing Engineering, Computer Science, Data Science, Electrical Engineering, or a related technical field.
  • Hands-on experience with SQL and Python — comfortable writing production queries and notebooks.
  • Familiarity with cloud analytics / data platforms (Databricks / Spark, Delta Lake, or similar).
  • Understanding of MES concepts and shop-floor data (OEE, takt time, cycle time, yield) and how to map MES signals to production events.
  • Basic data engineering skills: data modeling, time-series handling, data quality tests and monitoring.
  • Ability to work on the factory floor to gather requirements and validate dashboards / data (comfortable in a production environment).
  • Good communicator: able to partner across manufacturing, quality, supply chain, and software teams to define metrics and interpret results.
  • Strong problem solver: can take ambiguous manufacturing questions and produce reproducible data products and analyses.
  • Attention to detail and a documentation mindset: data contracts, lineage, and reproducible notebooks that others can run.

Nice To Haves

  • Databricks / Spark production experience, experience with MES systems (Siemens Opcenter, Tulip, etc.)
  • Previous experience as an intern in a production environment.

Responsibilities

  • Integrate MES / shop-floor data into a central analytics platform
  • Build near real-time production dashboards for operators and supervisors
  • Automate KPI calculations & alerts (OEE, first-pass yield, SPC)
  • Build & validate dashboards for pilot builds and line expansion
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