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Super Micro Computer

Modular, energy-efficient server hardware solutions

Sr. Software Quality Engineer

Data EngineeringUpdated on Nov 14
Full-timeBade District, TaiwanNo salary listedIn-person

About the Job

Requirements

  • At least 2 years of hands-on experience with Python 3 and proficiency in pandas, numpy, and related libraries for data processing and ETL.
  • Strong SQL and relational database skills, particularly PostgreSQL or Oracle or Microsoft SQL Server, including CTEs, window functions, UPSERT, schema design, and indexing.
  • Experience building and operating production ETL/ELT jobs using workflow or scheduling tools.
  • Knowledge of schema validation, deduplication, batch processing, and basic error handling and alerting for data quality.
  • Experience with Git branching workflows and configuration management.
  • Ability to discuss data requirements with engineering and operations teams in Chinese and English.
  • A BS or MS in Computer Science, Information Management, Electrical Engineering, Statistics, Mathematics, or a related technical field.

Responsibilities

  • Maintain and scale daily ETL/ELT pipelines using workflow or scheduling tools.
  • Build extractors for manufacturing reports in Excel, CSV, email attachment, and compressed archive formats.
  • Implement incremental loads with idempotent transforms, including deduplication, checkpoints, and rerun-safe jobs.
  • Optimize PostgreSQL batch ingestion using COPY or UPSERT for large volumes while maintaining stable memory use.
  • Monitor scheduled production runs and handle failures, alerting, and recovery.
  • Maintain backend data APIs and services that support analytics dashboards and reports.
  • Write and tune PostgreSQL queries, including CTEs and window functions, for operational and analytical use cases.
  • Support dashboard and reporting needs through KPI definition, trend analysis, and ad-hoc data requests.
  • Standardize manufacturing metrics such as station yield, First Pass Yield (FPY), and repair turnaround time (TAT).
  • Apply basic statistics or data science methods, such as anomaly detection or SPC-style quality tracking, when they improve insight.
  • Serve as the technical contact for data exchange with contract manufacturing sites.
  • Align report formats, column schemas, and naming standards with site engineering teams.
  • Improve data quality in incomplete or inconsistent fields, such as defect classification and part numbers.
  • Manage master data versioning, such as BOM, and coordinate automated report collection.
  • Investigate source-data issues, including template changes, corrupted files, and encoding or formatting errors.
  • Design and maintain warehouse layers, including staging, ODS, DW, and application summary tables.
  • Manage PostgreSQL schema changes, indexing, and routine database maintenance.
  • Enforce role-based access control for ETL, BI, and administrative users.
  • Maintain data quality checks, pipeline tests, and documentation.
  • Own historical backfill procedures, including backup, reset, reprocessing, and verification.

Desired Qualifications

  • Experience with web/API backend development, such as Python web frameworks, and dashboard or reporting services.
  • Experience with data warehousing, including staging, ODS, and DW layers and aggregate summary tables.
  • Experience with exploratory analysis, KPI definition, and manufacturing or quality metrics such as yield, FPY, TAT, and SPC.
  • Knowledge of data science fundamentals, including statistics, feature preparation, or basic machine learning for reporting and insight.
  • Experience parsing semi-structured files, including Excel, CSV, PDF, email attachments, and archives.
  • Experience with Windows Server, task scheduling, or Docker deployment.
  • Interest in LLM/RAG applications built on internal data platforms.

About the Company

Super Micro Computer

Modular, energy-efficient server hardware solutions

Super Micro Computer designs and sells high-performance, energy-efficient server hardware and related software and services for data centers, cloud, AI, 5G, and edge computing. Its modular Building Block Solutions let customers assemble configurable servers, storage, motherboards, and chassis from common components to match workloads. The company emphasizes green computing and power efficiency to reduce energy use in large-scale deployments and enable faster procurement. Its goal is to help customers deploy reliable computing infrastructure quickly through direct sales and an extensive partner network of distributors and value-added resellers.

Company size
5,001-10,000
Company stage
IPO
Headquarters
San Jose, CA
Founded
1993

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