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Supermicro
Supermicro
5001 – 10 000 Darbinieki
KonsultācijasLoģistikaRažošana
Supermicro izstrādā augstas veiktspējas skaitļošanas risinājumus, kuru pamatā ir serveru tehnoloģijas un moderna infrastruktūra uzņēmumu lietojumprogrammām. Uzņēmuma darbība aptver skaitļošanas tehnoloģiju nozari, apvienojot aparatūras inovācijas ar operatīvo pieredzi, kas nepieciešama prasīgu tehnoloģiju vides atbalstam. Profesionāļi, kurus interesē darbs serveru inženierijā, uzņēmumu skaitļošanas risinājumu jomā, ražošanā, loģistikā, konsultācijās un saistītās funkcijās, uzņēmumā Supermicro var sniegt ieguldījumu mūsdienu datu infrastruktūrā izmantotu produktu un sistēmu izstrādē.
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Vakances uzņēmumā

Software Quality Engineer, Manufacturing Data

Build ETL pipelines, PostgreSQL data services, and warehouse layers for Supermicro’s server and networking solutions. Support manufacturing analytics, quality metrics, and data governance across sites.

TWTaivānaKlātienēPilna slodzeJaunākais speciālistsVidējais līmenisNepieciešamā Valoda: angļuNepieciešamā Valoda: ķīniešuQA inženieris
DockerETLNumpyOraclePandasPostgresPythonSQL

Apraksts

  • Maintain and scale daily ETL/ELT pipelines with workflow and scheduling tools
  • Build extractors for manufacturing reports in Excel, CSV, email attachments, and compressed archives
  • Implement incremental loads with idempotent transformations, deduplication, checkpoints, and rerun-safe jobs
  • Optimize high-volume PostgreSQL batch ingestion with COPY and UPSERT while keeping memory use stable
  • Monitor production runs and manage failures, alerts, and recovery
  • Maintain backend data APIs and services for analytics dashboards and reports
  • Write and optimize PostgreSQL queries using CTEs and window functions
  • Support KPI definition, trend analysis, dashboards, reporting, and ad hoc data requests
  • Standardize manufacturing measures such as station yield, First Pass Yield (FPY), and repair turnaround time (TAT)
  • Use basic statistical and data science methods, including anomaly detection and SPC-style quality tracking
  • Serve as the technical contact for data exchanges with contract manufacturing sites
  • Align report formats, column schemas, and naming conventions with site engineering teams
  • Improve data quality in incomplete or inconsistent fields, including defect classifications and part numbers
  • Manage master data versioning, including BOMs, and coordinate automated report collection
  • Investigate source data problems such as template changes, corrupted files, and encoding or formatting errors
  • Design and maintain warehouse layers for staging, ODS, DW, and application summary tables
  • Manage PostgreSQL schema changes, indexing, and routine database maintenance
  • Apply role-based access controls for ETL, BI, and administrative users
  • Maintain data quality checks, pipeline tests, and documentation
  • Manage historical backfills, including backup, reset, reprocessing, and verification

Prasības

  • At least 2 years of hands-on Python 3 experience
  • Proficiency with pandas, NumPy, and related libraries for data processing and ETL
  • Strong SQL and relational database skills, especially with PostgreSQL or Oracle/MS SQL
  • Knowledge of CTEs, window functions, UPSERT, schema design, and indexing
  • Experience building and operating production ETL/ELT jobs with workflow or scheduling tools
  • Experience with schema validation, deduplication, batch processing, and basic error handling and alerting
  • Experience with Git branching workflows and configuration management
  • Ability to discuss data requirements with engineering and operations teams in Chinese and English
  • Bachelor’s or master’s degree in Computer Science, Information Management, Electrical Engineering, Statistics, Mathematics, or a related technical field
  • Preferred: Web or API backend development and dashboard or reporting services
  • Preferred: Data warehousing with staging, ODS, and DW layers, plus aggregate summary tables
  • Preferred: Exploratory analysis, KPI definition, and manufacturing or quality metrics such as yield, FPY, TAT, and SPC
  • Preferred: Statistics, feature preparation, or basic machine learning
  • Preferred: Parsing semi-structured files such as Excel, CSV, PDF, email attachments, and archives
  • Preferred: Windows Server, task scheduling, or Docker experience
  • Preferred: Interest in LLM or RAG applications on internal data platforms

Priekšrocības

  • The employer states an equal opportunity and diversity commitment
  • The posting refers to an “Our Benefits” section but does not specify individual benefits

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