Role at a glance
- Job function
-
AI & Data Data Engineering
- Salary
- $184K – $248.9K/yr
- Location
- Bellevue, Washington, United States
- Work arrangement
- Hybrid
- Employment
- Full-time
- Experience
- 10+ years of progressive experience in data strategy, data warehousing, business intelligence, or analytics engineering.
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Role Summary
This principal-level role owns the enterprise data strategy, AI, and new datamart vision across ERP-centric technology landscapes, including SAP, Oracle, and modern cloud data platforms. The leader connects enterprise data architecture, analytics, business intelligence, and AI while establishing a Manufacturing Operations Data Governance Council to align Engineering, Manufacturing, Supply Chain, and Finance.
What You'll Do
- Define the enterprise data strategy and roadmap for modernizing legacy data warehouses into cloud-native datamarts.
- Design datamart architectures, semantic layers, data fabrics, cloud data warehouses, pipelines, and orchestration across ERP and non-ERP...
- Charter and chair the Manufacturing Operations Data Governance Council, establishing data standards, ownership models, stewardship...
- Set strategic direction for enterprise reporting, analytics, KPI frameworks, visualization standards, and self-service analytics adoption.
- Identify and deliver generative AI, machine learning, forecasting, optimization, and intelligent automation use cases across enterprise...
- Partner with architecture, governance, integration, and business teams on clean-core strategies, ERP data orchestration, integration...
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Required
- 10+ years of progressive experience in data strategy, data warehousing, business
- intelligence, or analytics engineering.
- 5+ years of hands-on experience with enterprise application data ecosystems across one or
- more of: SAP (BW, HANA, Datasphere, S/4HANA), Oracle (EBS, Fusion, Oracle Cloud, OTBI),
- Microsoft Dynamics 365, or similar ERP platforms.
- Deep expertise in data modeling, semantic layer design, and building enterprise datamarts
- that unify data across multiple ERP systems.
- Proven experience designing and delivering AI/ML solutions in enterprise environments
Preferred
- Experience with modern ERP data platforms such as SAP Datasphere, Oracle Analytics Cloud,
- or Microsoft Fabric for enterprise data management.
- Familiarity with cloud-native ERP extensions — SAP BTP, Oracle Cloud Infrastructure, AWS,
- or Azure platform services.
- Experience integrating ERP data with Amazon Bedrock, Amazon Redshift, Amazon Q, or
- other AWS AI/analytics services.
- Background in ERP functional modules across Finance, Manufacturing, Supply Chain,
- Engineering, Order-to-Cash, Procurement, or Global Trade — on SAP, Oracle, or similar
Original job description
Content provided by the employer
Original job description
Content provided by the employer
New Datamart vision across our ERP-centric technology landscape. This role spans enterprise
platforms including SAP S/4HANA, Oracle Cloud Applications and similar ERP ecosystems leveraging
modern data platforms such as SAP Datasphere, Oracle Analytics Cloud, Databricks, Amazon
Redshift, or equivalent to build a unified, intelligent data fabric.
This leader will serve as the strategic bridge between enterprise data architecture, advanced
analytics, and business intelligence — translating complex, multi-Enterprise application data
landscapes into actionable, AI-powered insights at scale. The ideal candidate is platform-fluent but
platform-agnostic, able to design data strategies that harness the best of any enterprise application
ecosystem while maintaining a clean, governed, and extensible data foundation.
A critical mandate of this role is to establish and chair a Data Governance Council within
Manufacturing Operations, driving cross-functional alignment across Engineering, Manufacturing,
Supply Chain, and Finance to ensure data integrity, standardization, and actionable intelligence
throughout the manufacturing value chain.
Key job responsibilities
Enterprise Data Strategy & Datamart Architecture
• Define and own the enterprise data strategy across ERP-centric environments (SAP, Oracle,
or similar), establishing the roadmap for modernizing legacy data warehouses into cloud-
native datamarts.
• Design and implement a new Datamart architecture leveraging platforms such as SAP
Datasphere, Amazon Redshift, Aurora, unifying ERP and non-ERP data through virtualization,
replication, or hybrid approaches.
• Establish the semantic layer and business data fabric that preserves business context across
disparate enterprise systems, enabling consistent metrics, KPIs, and definitions across all
functional domains (Finance, Supply Chain, Manufacturing, Engineering, Order-to-Cash,
Procurement).
• Lead Data Modeling & Semantic Layer design — defining reusable business terms, metrics,
relationships, and associations that support analytics, planning, and AI/ML initiatives
regardless of the underlying ERP platform.
• Architect cloud data warehousing, data marts, and data pipelines & orchestration to
ensure scalable, performant, and governed data delivery from multiple ERP sources.
Own Data Quality & Governance frameworks ensuring data integrity, lineage, certification,
and lifecycle management across all enterprise datamarts and ERP systems — with
particular emphasis on Manufacturing Operations data standards.
Manufacturing Operations Data Governance Council
This role is accountable for chartering, establishing, and chairing a Data Governance Council within
Manufacturing Operations. The council will drive cross-functional data alignment and decision-
making across key operational domains:
• Charter and launch the Manufacturing Operations Data Governance Council, defining its
mission, scope, membership, decision rights, escalation paths, and cadence of reviews.
• Collaborate with Engineering to standardize product data definitions, BOM structures,
engineering change order data flows, and design-to-manufacturing data handoffs.
• Partner with Manufacturing to govern production data (MES, quality, yield, OEE), enforce
data standards across shop-floor systems, and enable real-time manufacturing analytics.
• Align with Supply Chain on demand planning data, inventory master data, logistics and
fulfillment metrics, and end-to-end supply chain visibility through governed data pipelines.
• Coordinate with Finance to ensure manufacturing cost data, variance analysis, standard
costing, and COGS reporting are underpinned by trusted, governed data from operational
systems.
• Define and enforce cross-functional data standards, data ownership models, stewardship
roles, and data quality SLAs across all council-participating functions.
• Establish a data issue resolution framework with clear escalation paths and accountability,
ensuring disputes over data definitions, ownership, and quality are resolved efficiently.
• Report governance health metrics to senior leadership, including data quality scorecards,
policy compliance rates, and council effectiveness KPIs.
Enterprise Reporting & Analytics
• Set the strategic direction for ERP-native reporting capabilities — including SAP Embedded
Analytics (Fiori), Oracle OTBI/BI Publisher, or equivalent built-in reporting tools.
• Drive the evolution of Enterprise Analytics & BI leveraging platforms such as SAP Analytics
Cloud (SAC), Oracle Analytics Cloud (OAC), Amazon QuickSight, Tableau, or Power BI for
dashboards, scorecards, planning, predictive analytics, and self-service analytics.
• Define and implement KPI Frameworks and Data Visualization standards, enabling insight-
to-action workflows across the enterprise independent of the source ERP system.
• Champion User Enablement & Adoption designing programs that democratize data access
and empower business users with self-service analytics capabilities across all ERP platforms.
• Standardize operational reporting, ad-hoc reporting, and embedded analytics patterns that
work consistently whether the source system is SAP, Oracle, or a third-party application.
AI & Advanced Analytics
• Identify, prioritize, and deliver Generative AI Use Cases for Enterprise Applications
leveraging AI services (e.g., Amazon Bedrock, Amazon Q, SAP Joule, Oracle AI, Azure OpenAI)
to embed intelligence into ERP-driven business processes.
• Build and scale Machine Learning Models for demand forecasting, supply chain
optimization, financial planning, anomaly detection, and process automation across ERP
platforms.
Drive Forecasting & Optimization initiatives that convert historical ERP data (from SAP,
Oracle, or similar) into predictive and prescriptive insights.
• Lead Intelligent Automation efforts automating repetitive data tasks, report generation, and
exception-based alerting through AI-powered workflows integrated with enterprise
applications.
• Establish AI governance frameworks ensuring responsible, compliant, and explainable AI
across all analytics use cases, regardless of the underlying ERP or data platform.
Integration & Platform Evolution
• Partner with Architecture & Governance teams to ensure alignment with clean core
strategy, extension strategies (e.g., SAP BTP, Oracle Cloud Infrastructure, AWS), and
integration standards.
• Collaborate with integration teams for data orchestration across cloud and on-premises ERP
systems — managing API gateways, event-driven architectures, and ETL/ELT pipelines.
• Drive platform evolution toward modern data architectures such as SAP Business Data
Cloud, Oracle Lakehouse, AWS Data Lake, Databricks Lakehouse — evaluating and road
mapping the best-fit architecture for the enterprise.
• Interface with Process & Business Excellence to translate business demand into data
solutions, ensuring tight alignment between business requirements and data architecture
decisions across all ERP systems.
Basic Qualifications
10+ years of progressive experience in data strategy, data warehousing, businessintelligence, or analytics engineering.
• 5+ years of hands-on experience with enterprise application data ecosystems across one or
more of: SAP (BW, HANA, Datasphere, S/4HANA), Oracle (EBS, Fusion, Oracle Cloud, OTBI),
Microsoft Dynamics 365, or similar ERP platforms.
• Deep expertise in data modeling, semantic layer design, and building enterprise datamarts
that unify data across multiple ERP systems.
• Proven experience designing and delivering AI/ML solutions in enterprise environments
(forecasting, optimization, NLP, or generative AI).
• Strong understanding of data governance, master data management, and data quality
frameworks in multi-system environments.
• Experience establishing and leading cross-functional data governance bodies, preferably
within Manufacturing or Operations environments spanning Engineering, Supply Chain, and
Finance.
• Experience with cloud data platforms (AWS Redshift/Glue/Lake Formation, Databricks,
Snowflake, Google BigQuery, or Azure Synapse) and modern data engineering tools.
• Track record of influencing senior leadership and driving strategic data initiatives across
large, complex organizations with heterogeneous ERP landscapes.
Preferred Qualifications
Experience with modern ERP data platforms such as SAP Datasphere, Oracle Analytics Cloud,or Microsoft Fabric for enterprise data management.
• Familiarity with cloud-native ERP extensions — SAP BTP, Oracle Cloud Infrastructure, AWS,
or Azure platform services.
• Experience integrating ERP data with Amazon Bedrock, Amazon Redshift, Amazon Q, or
other AWS AI/analytics services.
• Background in ERP functional modules across Finance, Manufacturing, Supply Chain,
Engineering, Order-to-Cash, Procurement, or Global Trade — on SAP, Oracle, or similar
platforms.
• Experience with enterprise planning & analytics platforms (SAP Analytics Cloud, Oracle
Planning Cloud, Adaptive Insights, Anaplan).
• Knowledge of Apache Iceberg, Delta Lake, Databricks Lakehouse, or other open data
lakehouse frameworks.
• Experience managing ERP data migration and modernization programs (e.g., SAP ECC to
S/4HANA, Oracle EBS to Fusion Cloud, or multi-ERP consolidation).
• Relevant certifications in enterprise data platforms (SAP, Oracle, AWS Data Analytics,
Databricks, Snowflake).
• Experience standing up data governance councils in manufacturing or industrial settings with
demonstrated impact on data quality and cross-functional alignment
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Bellevue - 184,000.00 - 248,900.00 USD annually
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.