Analytics Engineering Lead

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OtherEngineering Lead

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Quick Summary

Key Responsibilities

Partner with IT, enterprise architecture, and platform enablement teams to scale the Global Operations enterprise data lakehouse and reporting ecosystem.

Technical Tools

OtherEngineering Lead

The Analytics Engineering Lead, within the Operations Intelligence & Analytics organization, orchestrates the transformation of complex, raw data into trusted, business-ready data assets that power executive dashboards, performance metrics and advanced analytics across Global Operations. Working at the intersection of data engineering and business analytics, this role applies modern software engineering and data modeling practices to develop enterprise-grade data products that support decision-making across Global Operations while advancing the maturity of the organization's data lakehouse ecosystem.

As a key partner to leaders across Supply Chain, Manufacturing, Quality, Regulatory Affairs, and other Global Operations functions, the Analytics Engineering Lead combines deep technical expertise with strong business acumen to translate strategic priorities into reusable, high-value data solutions. Through close collaboration with cross-functional stakeholders, this role enables scalable analytics, strengthens data foundations, and accelerates the organization's digital, AI, and data science capabilities.

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, CI/CD, 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.

Requirements

~2 min read

Bachelor's degree in Data Engineering, Data Science, Computer Science, Statistics, or a related field, or equivalent professional experience; Master's degree preferred.
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/PySpark, with experience building scalable data pipelines, lakehouse architectures, and governed data products.
Highly experienced with modern cloud data platforms such as Microsoft Fabric, Databricks, Snowflake, or equivalent technologies, including orchestration and transformation frameworks.
Demonstrated 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, AI solutions.
Strong understanding of ERP and operational business processes, including SAP ECC data structures and modules such as MM, PP, QM, and SD; familiarity with Oracle Agile PLM is preferred.
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.

Preferred Qualifications:

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.

This job has a full time weekly schedule. Applications for this job will be accepted until at least October 14, 2026 or until the job is no longer posted.

The full-time equivalent pay range for this position is $143,760.00 - $269,550.00/yr plus eligibility for bonus, stock and benefits. Our pay ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. During the hiring process, a recruiter can share more about the specific pay range for a preferred location. Pay and benefit information by country are available at: https://careers.agilent.com/locations

Agilent Technologies, Inc. is an Equal Employment Opportunity and merit-based employer that values individuals of all backgrounds at all levels. All individuals, regardless of personal characteristics, are encouraged to apply. All qualified applicants will receive consideration for employment without regard to sex, pregnancy, race, religion or religious creed, color, gender, gender identity, gender expression, national origin, ancestry, physical or mental disability, medical condition, genetic information, marital status, registered domestic partner status, age, sexual orientation, military or veteran status, protected veteran status, or any other basis protected by federal, state, local law, ordinance, or regulation and will not be discriminated against on these bases. Agilent Technologies, Inc., is committed to creating and maintaining an inclusive in the workplace where everyone is welcome, and strives to support candidates with disabilities. If you have a disability and need assistance with any part of the application or interview process or have questions about workplace accessibility, please email job_posting@agilent.com or contact +1-262-754-5030. For more information about equal employment opportunity protections, please visit www.agilent.com/en/accessibility.

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