Principal, Enterprise Data Strategy, AI & Analytics, Amazon Leo

Relha LLC; Bellevue, Northern (WA, KY); Hybrid; USD 184,000 - 249,000; Full time

Job summary

Amazon is seeking a principal-level leader to own the Enterprise Data Strategy, AI, and Datamart vision across ERP-centric platforms. You will bridge data architecture and business insights, driving data governance, standardization, and AI-powered analytics at scale.

The role requires platform fluency across SAP, Oracle, and cloud data platforms, and a track record of cross-functional leadership with manufacturing and operations teams.

Qualifications

• 10+ years leading data strategy, governance, and analytics in enterprise settings.
• Experience with ERP ecosystems (SAP, Oracle) and cloud data platforms.
• Track record delivering enterprise datamarts and AI-enabled analytics.

Responsibilities

• Define and own the enterprise data strategy across ERP environments.
• Lead Datamart architecture and modern data platform implementations.
• Chair the Manufacturing Operations Data Governance Council.
• Drive AI/ML initiatives and governance across ERP platforms.

Skills

Data strategy

Enterprise data

AI & analytics

Datamart architecture

Data governance

ERP platforms (SAP/Oracle)

Education

10+ years data leadership

Tools

SAP S/4HANA

SAP Datasphere

Oracle Cloud Applications

Databricks

Amazon Redshift

Power BI/Tableau

Job description

Principal, Enterprise Data Strategy, AI & Analytics, Amazon Leo

We are seeking a principal-level (L7) leader to own and drive the Enterprise Data Strategy, AI, and

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-

• 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).

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.
• 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

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, 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

(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,

• 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).

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.

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