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Agilent Technologies

Provides eProcurement automation and hosted catalogs

Analytics Engineering Lead

Data EngineeringUpdated on Nov 12
Full-timeIn-person

About the Job

Requirements

  • A bachelor's degree in Data Engineering, Data Science, Computer Science, Statistics, or a related field, or equivalent professional experience.
  • At least 8 years of experience in analytics engineering, data modeling, data warehousing, or data platform development, with deep expertise in dimensional modeling and modern data architectures.
  • Expert-level SQL and strong proficiency in Python and PySpark, with experience building scalable data pipelines, lakehouse architectures, and governed data products.
  • Extensive experience with modern cloud data platforms such as Microsoft Fabric, Databricks, Snowflake, or equivalent technologies, including orchestration and transformation frameworks.
  • Experience architecting enterprise data products, governance frameworks, and reusable analytical assets, including KPI frameworks, metadata, and data quality controls, to support scalable analytics, machine learning, and AI solutions.
  • Strong understanding of ERP and operational business processes, including SAP ECC data structures and modules such as MM, PP, QM, and SD.
  • Ability to influence technical and business stakeholders and communicate architectural concepts across a matrixed organization.
  • Experience leveraging DevOps and collaboration platforms, including GitHub, Confluence, and Jira, to support agile delivery, version control, documentation, and product lifecycle management.

Responsibilities

  • Partner with IT, enterprise architecture, and platform enablement teams to scale the Global Operations enterprise data lakehouse and reporting ecosystem.
  • Own the Global Operations analytical data architecture, including silver- and gold-layer data products, dimensional models, semantic assets, and integration patterns aligned with enterprise standards.
  • Design and build cleansed, conformed, and consumption-ready data products that integrate data across enterprise systems and support executive reporting, analytics, and decision intelligence.
  • Develop and govern certified semantic models, standardized KPI frameworks, and reusable business logic that establish a single source of truth for performance measurement across Global Operations.
  • Implement data governance practices, including data quality controls, reconciliation, metadata, lineage, certification, and ownership standards, to ensure trusted reporting assets.
  • Automate and optimize data transformation workflows using SQL, Python, PySpark, and cloud-native data engineering services.
  • Establish DataOps and platform management practices, including source control, automated testing, continuous integration and continuous delivery, monitoring, performance optimization, security controls, and production support.
  • Design AI-ready data products and knowledge assets that support advanced analytics, machine learning, generative AI, and decision intelligence capabilities.

Desired Qualifications

  • A master's degree is preferred.
  • Familiarity with Oracle Agile PLM is preferred.
  • Previous experience supporting global supply chain, manufacturing, quality, or regulatory operations in a complex enterprise environment.
  • Experience supporting ERP modernization initiatives, including legacy ERP environments, system consolidations, data migrations, and transformation of enterprise data assets to modern analytics platforms.
  • Experience driving adoption of enterprise data products, governance practices, and self-service analytics capabilities.
  • Relevant Microsoft Fabric, cloud, or data engineering certifications such as MS DP-600 or MS DP-700.

About the Company

Agilent Technologies

Provides eProcurement automation and hosted catalogs

Agilent Technologies provides eProcurement services that help businesses buy supplies more efficiently. It offers a suite of electronic procurement tools that let clients load their pricing into existing purchasing platforms, access a hosted catalog, and complete transactions digitally without paper. The service connects pricing data to clients’ procurement systems, delivers an online catalog, and supports automated, paperless purchasing workflows. This makes purchasing faster and reduces manual steps. Compared with competitors, Agilent emphasizes automation, quick connectivity between pricing, catalogs, and purchasing platforms, and a reliable, scalable experience backed by its broad product range. The company aims to improve client productivity and lower procurement costs, helping customers buy what they need more easily while keeping prices clear and consistent.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1999

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