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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.
Сипаттама
- 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.
Талаптар
- 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.
Артықшылықтар
- Eligibility for a bonus.
- Eligibility for stock awards.
- Employee benefits package.
- Travel requirement of 10%.
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