Senior Data Engineer

TEKsystems•San Jose, CA

13h•$100 - $130•Remote

About The Position

About the Role The team needs a senior Databricks-focused data engineer who can design scalable, multi‑site data architecture supporting the long-term roadmap toward AI, context engineering, and continuous data-product evolution. This person must have strong data modeling, Databricks expertise, and a solid understanding of data governance, including how controls are applied on pipelines and how architectural decisions reinforce governance standards. The role involves no maintenance work; it is fully focused on a simultaneous rollout of six sites, continuously integrating new datasets and ensuring the architecture scales as additional factories and business units come online. This requires someone who can think big-picture, avoid rebuilds, and ensure the architecture supports future growth without rework. They must also be confident and diplomatic enough to push back on highly experienced data scientists, who currently handle much of the modeling and data landing themselves. The engineer needs to represent the broader vision, guide conversations, and ensure alignment across the team—not simply take orders. The team already has execution-level data engineers and support from Databricks’ practice group, so what’s needed is a strategic leader, not another ticket‑based executor. Needs strong understanding of data governance, pipeline controls, and be able to explain how that impacts architectural decisions. Lumentum is seeking a Data Engineer to help centralize and optimize data across six manufacturing factories and fabs. Currently, reporting is siloed, and systems are isolated. This role will focus on extracting data from multiple sources, consolidating it into a centralized data lake (Databricks), and enabling advanced analytics and machine learning models for improved manufacturing efficiency.

Requirements

Database expertise and strong knowledge of AWS cloud services.
Experience with data modeling and modern data architecture principles.
Familiarity with manufacturing systems (MES) and related operational data.
Prior experience in semiconductor or high-tech manufacturing companies (e.g., Texas Instruments, Applied Materials).
Ability to understand manufacturing processes and associated performance metrics.
Proficiency in Databricks or similar platforms for data engineering.
Strong SQL and data integration skills; ability to pull and transform data rather than just build metrics.

Responsibilities

Extract and integrate data from diverse manufacturing systems (MES and related platforms) into a centralized data lake.
Design and implement scalable data models and architectures to support analytics and AI/ML initiatives.
Collaborate with data scientists to prepare structured datasets for machine learning and predictive analytics.
Work closely with manufacturing teams to understand processes, metrics, and data flows.
Ensure data quality, consistency, and accessibility across multiple sites.