Job description

Sanmina Corporation (Nasdaq: SANM) is a leading integrated manufacturing solutions provider serving the fastest-growing segments of the global Electronics Manufacturing Services (EMS) market. Recognized as a technology leader, Sanmina Corporation provides end-to-end manufacturing solutions, delivering superior quality and support to Original Equipment Manufacturers (OEMs) primarily in the communications networks, defense and aerospace, industrial and semiconductor systems, medical, multimedia, computing and storage, automotive and clean technology sectors. Sanmina Corporation has facilities strategically located in key regions throughout the world. Manufacturing Data Analyst (Data Tech) Role Summary We are seeking a Manufacturing Data Analyst to be the "data architect" for our electronics manufacturing facility. This role sits at the critical intersection of the Prototyping to Production pipeline. You will be responsible for hunting down data from diverse manufacturing equipment, parsing disparate file types, and building the automated reporting infrastructure that defines our success. The ideal candidate is part data detective and part automation enthusiast—someone who isn't afraid to manually build a report today while writing the Python script to automate it tomorrow. Key Responsibilities • Data Acquisition: • Identify and extract data from SMT lines, AOI, AXI, and functional test fixtures. • Work with equipment vendors to unlock data access or develop custom reporting exports. • Parse and clean "messy" data from flat files (CSV, XML, JSON) and MES databases. • Performance Metrics & Statistical Analysis: • Develop and maintain reports for First Pass Yield (FPY) , Parametric Test Trends , and Process Capability (Cpk) . • Visualize data distributions to help engineers identify "drift" during the prototyping and manufacturing phases. • Reporting Automation: Design and implement Python scripts or BI tools to replace manual Excel-based workflows. • Standardize reporting formats across different product lines. • Cross-Functional Collaboration: Present findings to Engineering and NPI (New Product Introduction) teams to drive design changes that improve manufacturability. Technical Requirements & Qualifications Data Engineering & Automation • Scripting: Advanced knowledge of Python (Pandas, NumPy, OpenPyXL) to parse raw data from flat files (CSV, XML, JSON, TXT). • Databases: Experience writing SQL queries to extract data from MES or local SQL Express instances. • Architecture: Proven ability to transition manual "copy-paste" processes into automated pipelines. Manufacturing & Hardware Context • Integration: Experience navigating proprietary machine software to locate and export data logs (SMT, AOI, Functional Test). • NPI Cycle: Familiarity with the urgency and data-fluidity of the New Product Introduction phase. • Vendor Liaison: Ability to communicate technical data requirements to equipment manufacturers. Statistical Analysis • SPC Knowledge: Solid grasp of Mean, Standard Deviation, and Variance. • Calculations: Expert ability to interpret FPY, RTY, Cp, and Cpk • Parametric Analysis: Ability to analyze continuous data (voltages, timing, resistance) to identify trends before they result in failures. Education/Experience: 2+ years in a manufacturing environment (Electronics preferred) with a degree in Engineering, Data Science, or a related technical field. Sanmina is an Equal Opportunity Employer Why This Role Matters During the Prototyping Phase, data is often fragmented and chaotic. You will be the person who organizes that chaos into a roadmap for high-volume production. Your reports won't just be "look-back" summaries; they will be the tools we use to fix the product and process before release to manufacturing.

Requirements

Must-haves

Manufacturing Data Analyst (Data Tech)
The ideal candidate is part data detective and part automation enthusiast—someone who isn't afraid to manually build a report today while writing the Python script to automate it tomorrow.
Identify and extract data from SMT lines, AOI, AXI, and functional test fixtures.
Work with equipment vendors to unlock data access or develop custom reporting exports.
Parse and clean "messy" data from flat files (CSV, XML, JSON) and MES databases.
Develop and maintain reports for First Pass Yield (FPY) , Parametric Test Trends , and Process Capability (Cpk) .
Visualize data distributions to help engineers identify "drift" during the prototyping and manufacturing phases.
Reporting Automation: Design and implement Python scripts or BI tools to replace manual Excel-based workflows.
Standardize reporting formats across different product lines.
Cross-Functional Collaboration: Present findings to Engineering and NPI (New Product Introduction) teams to drive design changes that improve manufacturability.
Technical Requirements & Qualifications
Data Engineering & Automation
Scripting: Advanced knowledge of Python (Pandas, NumPy, OpenPyXL) to parse raw data from flat files (CSV, XML, JSON, TXT).
Databases: Experience writing SQL queries to extract data from MES or local SQL Express instances.
Architecture: Proven ability to transition manual "copy-paste" processes into automated pipelines.
Manufacturing & Hardware Context
Integration: Experience navigating proprietary machine software to locate and export data logs (SMT, AOI, Functional Test).
NPI Cycle: Familiarity with the urgency and data-fluidity of the New Product Introduction phase.
Vendor Liaison: Ability to communicate technical data requirements to equipment manufacturers.
Statistical Analysis
SPC Knowledge: Solid grasp of Mean, Standard Deviation, and Variance.
Calculations: Expert ability to interpret FPY, RTY, Cp, and Cpk
Parametric Analysis: Ability to analyze continuous data (voltages, timing, resistance) to identify trends before they result in failures.

Nice-to-haves

Education/Experience: 2+ years in a manufacturing environment (Electronics preferred) with a degree in Engineering, Data Science, or a related technical field.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

pythonsql

Platform: sanmina
Effort: medium