Agilent Technologies
Agilent Technologies
Agilent Technologies biofarmatsevtik tadqiqotlar, oziq-ovqat va ichimliklarni sinash, klinik diagnostika hamda atrof-muhit tahlilida qo‘llaniladigan analitik va laboratoriya texnologiyalarini ishlab chiqadi. Kompaniya portfeliga gaz va suyuqlik xromatografiyasi, mass-spektrometriya, laboratoriya jihozlari, dasturiy ta’minot va informatika yechimlari kiradi. Ular laboratoriyalarni boshqarish, texnik xizmat ko‘rsatish va asboblarni ta’mirlash xizmatlari bilan qo‘llab-quvvatlanadi. Kompaniya ushbu texnologiyalarni genomika, patologiya va saraton tadqiqotlarida ham qo‘llab, barqaror yechimlar orqali ilm-fan taraqqiyotiga hissa qo‘shishga e’tibor qaratadi.

Analytics Engineering Lead - Agilent Technologies - Santa Clara Onsite

Lead the development of governed lakehouse data products for Agilent Technologies’ global operations. Enable executive reporting, AI initiatives, and decision intelligence across supply chain and manufacturing.

Tavsif

  • Collaborate with IT, enterprise architecture, and platform enablement teams to expand the Global Operations data lakehouse and reporting environment.
  • Lead analytical data architecture for Global Operations, spanning silver- and gold-layer products, dimensional models, semantic assets, and integration patterns.
  • Create cleansed, conformed, consumption-ready data products from enterprise-system data.
  • Build and oversee certified semantic models, common KPI definitions, and reusable business logic.
  • Apply governance controls for data quality, reconciliation, metadata, lineage, certification, and ownership.
  • Automate and improve transformation workflows with SQL, Python, PySpark, and cloud-native engineering services.
  • Establish DataOps and platform management practices covering version control, automated testing, CI/CD, monitoring, performance, security, and production support.
  • Develop AI-ready data products and knowledge assets for advanced analytics, machine learning, generative AI, and decision intelligence.

Talablar

  • Bachelor’s degree in data engineering, data science, computer science, statistics, or a related discipline, or equivalent professional experience.
  • At least eight years of experience in analytics engineering, data modeling, data warehousing, or data platform development.
  • Advanced knowledge of dimensional modeling and modern data architecture.
  • Expert SQL skills with strong Python and PySpark capability.
  • Background designing scalable pipelines, lakehouse architectures, and governed data products.
  • Experience with Microsoft Fabric, Databricks, Snowflake, or comparable platforms, including orchestration and transformation frameworks.
  • Experience architecting enterprise data products, governance frameworks, and reusable analytical assets such as KPI frameworks, metadata, and data quality controls.
  • Strong understanding of ERP and operational processes, including SAP ECC structures and the MM, PP, QM, and SD modules.
  • Ability to align technical and business stakeholders and explain architecture within a matrixed organization.
  • Experience using GitHub, Confluence, and Jira.
  • Master’s degree preferred.
  • Familiarity with Oracle Agile PLM preferred.
  • Experience supporting global supply chain, manufacturing, quality, or regulatory operations preferred.
  • Experience contributing to ERP modernization programs preferred.
  • Experience increasing adoption of enterprise data products, governance practices, and self-service analytics preferred.
  • Relevant Microsoft Fabric, cloud, or data engineering certifications, including MS DP-600 or MS DP-700, preferred.

Imtiyozlar

  • Eligibility for a bonus.
  • Eligibility for stock awards.
  • Employee benefits package.
  • Travel requirement of 10%.

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