Analytics Engineering Lead

Agilent seeks an Analytics Engineering Lead to transform raw operational data into trusted business assets supporting executive decision-making across global operations. This role combines data engineering expertise with business acumen to develop enterprise-grade data products, establish governance frameworks, and advance the organization's data lakehouse and AI capabilities.

Responsibilities

• Partner with IT and enterprise teams to scale Global Operations data lakehouse and reporting ecosystem
• Own analytical data architecture including silver/gold-layer products, dimensional models, and semantic assets
• Design cleansed, conformed data products integrating enterprise systems for executive reporting and decision intelligence
• Develop certified semantic models, KPI frameworks, and business logic establishing single source of truth for performance measurement
• Implement data governance practices including quality controls, reconciliation, metadata, lineage, and certification standards

Requirements

• Bachelor's degree in Data Engineering, Data Science, Computer Science, Statistics, or related field; Master's preferred
• 8+ years analytics engineering, data modeling, data warehousing, or data platform development experience
• Expert SQL and strong Python/PySpark proficiency for scalable data pipelines and lakehouse architectures
• Deep experience with modern cloud platforms: Microsoft Fabric, Databricks, Snowflake, or equivalent
• Demonstrated expertise architecting enterprise data products with governance, KPI frameworks, and data quality controls
• Strong understanding of ERP systems, SAP ECC modules (MM, PP, QM, SD); Oracle Agile PLM knowledge preferred
• Ability to influence stakeholders and communicate technical concepts across matrixed organizations

Compensation: $143,760-$269,550/yr plus eligibility for bonus, stock and benefits