Motorola Solutions
PrincipalAIDataStrategyLead
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optimal for Lead candidates.
“Principal AI Data Strategy Lead at Motorola Solutions. Skills: AI data architecture, Data governance, Data quality, Data cataloging. Define enterprise AI data architecture vision. Define principles and reference architectures”
What You'll Achieve.
Make structured and unstructured data trustworthy; Make structured and unstructured data discoverable; Make structured and unstructured data easy to consume; Improve joinability and reuse across domains; Prevent sensitive data exposure; Enable informed cost/performance choices by consumers; Improve efficiency
What They're Looking For.
Must Have
8+ years in data engineering/architecture/platform roles, Expert SQL, track record building enterprise data governance, contracts, and quality frameworks, Experience operating production data platforms in batch/near-real-time with lineage and access control, Practical unstructured data governance (metadata standards, classification, PII detection/redaction), Hands-on with catalogs/lineage as systems of record for definitions, ownership, and policy, Experience with workflow orchestration (e.g. Airflow), CI/CD/testing for data pipelines
Nice to Have
>1 year at Staff/Principal level, Familiarity with vector/RAG readiness concepts (schemas, metadata, provenance) without owning embeddings/model development
What You'll Do.
Define enterprise AI data architecture vision
Define principles and reference architectures
Establish data contracts for AI consumption
Govern schema evolution
Make data catalog system of record
Integrate with intake/change management
Define standard data models
Define semantic conventions
Implement enterprise data quality framework
Implement automated scorecards
Monitor for anomalies
Publish AI data readiness dashboards
Standardize patterns for ingestion
Standardize patterns for processing
Standardize patterns for storage
Standardize patterns for serving
Standardize patterns for environment promotion
Define secure access patterns
Define consistent access APIs
Drive foundational architecture for RAG
Drive foundational architecture for semantic search
Provide guidance for chunking policies
Provide guidance for deduplication
Provide guidance for hybrid search
Define safe-access patterns for AI consumption
Enforce security baselines
Enforce policy-as-code for access
Architect for transparent cost attribution
Architect for transparent cost controls
Assist leadership with recommendations
Create automated triggers for budget violations
Provide reference templates for AI-ready datasets
Provide reference templates for contracts
Provide reference templates for catalog
Mentor engineers and analysts on best practices
Collaborate with system architects
How You'll Work.
Team & Collaboration
Lead cross-functional reviews with IT, security, legal/privacy, and business stakeholders; Collaborate with other system architects
Full Job Description
## **Company Overview** At Motorola Solutions, we believe that everything starts with our people. We’re a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that’s critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future. ## **Department Overview** Operates the centralized data warehouse for all of Motorola Solutions. ## Job Description We are seeking a Staff/Principal AI Data Lead to modernize our enterprise data ecosystem so it is ready to support building new AI and ML tools(e.g., automated classification/summarization, agentic workflows, and RAG for example). This role focuses on data readiness, governance, quality, and secure access. You will define the standards, contracts, and observability that make structured and unstructured data trustworthy, discoverable, and easy to consume in batch and near-real-time contexts. Decisions about orchestration tooling are to be determined, but we are currently focusing on using an Airflow-centric approach. The person in this role will help make decisions about data infrastructure implementation and tooling. # **Responsibilities** ## **Strategy and Standards** * Define the enterprise AI data architecture vision, principles, and reference architectures. * Lead cross-functional reviews with IT, security, legal/privacy, and business stakeholders to align on data readiness roadmaps**.** ## **Data Contracts, Catalog, and Modeling** * Establish data contracts for AI consumption (schemas, semantics, classifications, SLAs) and govern schema evolution for backward compatibility. * Make the data catalog the system of record for lineage, ownership, definitions, and policy labels; integrate with intake/change management. * Define standard data models
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