Senior Manager - Data Digitalization Architecture

LEAR CORPORATION; Southfield (MI); On-site; USD 140,000 - 190,000; Full time

Job summary

Lear Corporation in Southfield, MI seeks a Senior Manager to drive Data & Digitalization Architecture, translating source-system data into governedFoundry/Palantir models. You will partner with ERP owners, FDEs, Ontologists, IT, and Data Governance to map inputs from SAP, QAD, MES, and finance into global reusable domain objects and data products.

You will define data grain, lineage, security classifications, and governance rules, ensuring build-ready mappings across Procurement, Supply Chain,

Qualifications

• Strong business process knowledge across procurement, supply chain, manufacturing and finance.
• Experience interpreting ERP/source-system data structures and field meaning.
• Ability to translate between business SMEs, technical data teams, ontology/modeling teams and stakeholders.
• Understanding of data domains, lineage, metadata, and master/golden records.
• Working knowledge of data governance and security controls.

Responsibilities

• Lead source-to-ontology mapping and preserve global reusable domain models.
• Document source tables, fields, structures, and update cadence with ERP owners.
• Define data grain, refresh cadence, lineage, and data quality criteria.
• Collaborate with Ontology Owner/Ontologist to avoid duplicate object types.
• Define field security classifications and access requirements.
• Support MVP/POC reviews ensuring mapping readiness for production.

Skills

Procurement knowledge

ERP data interpretation

Business-translation

Data governance

Security/RBAC

Job description

Senior Manager - Data Digitalization Architecture

Location: Southfield, MI, US, 48033

Country/Region: United States

Job Function: Manufacturing

Requisition ID: 48832

Lear For You

We work hard for the people who work for us. We champion our teams and foster collaboration, inclusion, respect and excellence. Because we want to be more for you.

A path to a better career. A better future.

Our teams have invented groundbreaking technologies, manufactured millions of products and earned a long list of awards. Year after year, we're named one of the Worlds Most Admired Companies.

They're the secret to our success - empowered, inventive and inclusive. Passionate about their craft. Driven to succeed. Because we win together.

Are you ready for a better career? A better future?

Job Description

Lead the translation of Lear's source-system data into governed, reusable Foundry / Palantir ontology objects, properties, links, actions, and data products. Partner with business process owners, ERP/source-system owners, Foundry FDEs, Ontologists, IT/Data Engineering, Data Governance, Security/RBAC, and project teams to ensure that data from QAD, SAP, Plex, AS400/BPICS, PLM/SEM, SRM, MES, finance, quality, and supplier-facing inputs is consistently mapped to global reusable business objects and properties. The Senior Manager of Data & Digitalization (Data Architecture) is a cross-functional business-data translation role responsible for creating build-ready source-to-ontology mapping specifications and ensuring that Lear's Foundry builds use global, reusable domain models rather than siloed project-specific data definitions. This role will work across Procurement, Supply Chain, Engineering, Quality, Finance, Manufacturing, IT, and Data Governance to interpret business process requirements, source-system field meaning, data grain, refresh cadence, lineage, data quality rules, security classification, and source-of-record precedence.

Responsibilities

• Partner with BPOs and business SMEs to understand business processes, use cases, workflows, decision points, KPIs, and approval rules.
• Partner with ERP/source-system owners to document source tables, fields, structures, extracts, APIs, files, field behavior, known defects, and update cadence.
• Create and maintain source-to-ontology mapping specifications from source fields to Foundry global objects, properties, links, actions, and data products.
• Determine whether a data element should reuse an existing global object/property, create a new governed global property, become a derived property, or remain a local workflow-specific field.
• Document source-of-record, survivorship, and precedence rules when multiple sources provide different values for the same business property.
• Define data grain, refresh cadence, event triggers, transformation rules, lineage/provenance, data quality expectations, and UAT validation criteria.
• Work with the Ontology Owner/Ontologist to prevent duplicate object types and avoid source-table-driven object models or one to one uncurated source-column mappings.
• Define field/property-level security classifications including supplier-visible, internal-only, protected commercial, finance/legal restricted, and role-based access requirements.
• Support action/writeback design by identifying when supplier responses, buyer updates, exception closures, tooling classifications, or approvals require governed Foundry Actions rather than direct edits.
• Maintain a reusable enterprise mapping library by domain, including Supplier, Supplier Site, Plant/Site, Item/Part, BOM, Demand, Capacity, Tooling, PO, Receipt, Invoice, Contract, RFQ, Quality, Risk, and Workflow/Exception.
• Support MVP, POC, PCO, sprint, UAT, and go-live reviews by confirming that data meaning, mapping, reuse, security, and lineage are ready for production use.

Your Qualifications

• Strong business process knowledge in procurement, supply chain, sourcing, capacity planning, supplier management, BOM/product structure, launch readiness, manufacturing operations, quality, finance/commercial, or adjacent enterprise processes.
• Experience interpreting ERP/source-system data structures and field meaning. Preferred exposure includes QAD, SAP, Plex, AS400/BPICS, PLM/SEM, SRM, MES, supplier portals, finance, quality, or procurement platforms.
• Ability to translate between business SMEs, technical data teams, ontology/modeling teams, IT, ERP owners, and executive stakeholders.
• Understanding of data domains, objects, properties, relationships, data grain, lineage, metadata, data quality, source-of-record decisions, and master/golden record concepts.
• Working knowledge of data governance, data stewardship, security/RBAC, protected commercial data, supplier-facing access rules, and change control.