Leader of AI & Data Platforms

Ralliant•Chandler, AZ

8h•Onsite

About The Position

PacSci EMC is seeking a hands-on AI engineering leader to accelerate enterprise AI adoption and build the governed data foundations that enable practical, secure business solutions. This leader personally develops, deploys, and sustains production AI and data capabilities while leading a small team across data engineering, architecture, and application and analytics development. The AI and Data Leader leads technical architecture and data readiness for the Palantir Foundry initiative in partnership with the business SME leader and PMO, while advancing enterprise data stewardship, lifecycle management, and self-service tools. The role combines technical execution, team development, and executive influence in an evolving environment. It also participates in the Ralliant Technology & Growth Council, with up to 20% allocation, contributing to enterprise architecture reviews, innovation, standards, and cross-operating-company technology direction.

Requirements

5+ years in analytics, data platforms, AI enablement, or data governance roles, with proven hands-on delivery.
Demonstrated personal experience building, deploying, and sustaining production AI and data solutions, including production-grade pipelines and appropriate operational safeguards.
Strong hands-on proficiency with SQL and Python/PySpark; experience with data modeling, orchestration, and observability.
Experience with Microsoft Purview and enterprise data governance, stewardship, or lifecycle management.
Demonstrated ability to learn enterprise data platforms, guide architectural decisions, and coordinate technical delivery across business and technology teams.
Working knowledge of Power BI or similar analytics tools and the ability to partner with developers on governed self-service analytics.
Strong cross-functional influence and executive communication; ability to explain technical concepts clearly to non-technical audiences and support recommendations with evidence and business impact.
Ability to lead technical work, coach colleagues, and collaborate effectively while remaining personally involved in engineering and delivery.
Comfort operating in an evolving environment, prioritizing amid ambiguity, developing practical prototypes, and carrying solutions through implementation and ongoing support.

Nice To Haves

Experience with Palantir Foundry, including pipelines, ontology, and application development; strongly preferred.
Background in aerospace and defense or other highly regulated industries with strict data and compliance requirements, such as ITAR, FAR/DFARS, or DCAA.
Familiarity with controlled unclassified information (CUI), FedRAMP requirements, and secure cloud deployment practices.
Working knowledge of SCADA/OT data environments, ERP/MES/PLM data structures, and manufacturing execution workflows.
Experience building AI or data capabilities in a startup, technology disruptor, or similarly resource-constrained environment, with demonstrated implementation results.
Familiarity with Lean principles and structured problem solving; ability to balance rapid delivery with compliance and sustainable operations.

Responsibilities

Evaluate and recommend secure, compliant AI tools; personally implement and operationalize priority solutions that improve productivity and enable business teams to use AI effectively.
Identify and prioritize AI opportunities across Planning, Buying, Manufacturing Operations, Factory Management, Engineering, PMO, and other business functions; translate operating challenges into practical solutions and measurable outcomes.
Lead and develop a small team across data engineering, architecture, and Power BI/Power Platform development; provide technical coaching, establish delivery priorities, and build team capability as business needs evolve.
Lead technical architecture, data readiness, and implementation support for Palantir Foundry in partnership with the business SME leader, who retains overall program delivery accountability, and PMO; coordinate appropriate technology resources and architectural decisions.
Establish enterprise data warehousing, stewardship, and lifecycle-management practices, including labeling, lineage, retention, role-based access, auditability, and clearly defined data ownership.
Use Microsoft Purview to support data governance and lifecycle-management practices across priority data domains.
Build and maintain production-grade pipelines, transformations, data models, and reusable integration patterns; develop governed ontologies, lightweight applications, and self-service data products as business priorities require.
Partner with manufacturing engineering and other technical specialists on SCADA/OT data integration, reference data products, and anomaly-detection use cases; establish data architecture standards and document interfaces and operational runbooks.
Enable business users through training, practical playbooks, quick-start templates, and hands-on collaboration; support citizen development within appropriate access and compliance guardrails.
Partner with analytics developers to deliver dashboards, signals, and triggers that improve operational visibility and actionability, including order execution and cost tracking.
Own reliability of AI and data assets through monitoring, observability, performance tuning, troubleshooting, and ongoing production support; implement reusable quality checks and alerts.
Present technology options and recommendations to leaders with clear cost, impact, risk, and implementation tradeoffs; collaborate on decisions and balance immediate delivery needs with enterprise standards.
Define baselines and track solution adoption and business impact, including hours saved, manual effort reduced, automated transactions, efficiency, revenue enablement, and supply-chain execution performance.
Maintain an actionable opportunity backlog, data product catalog, access reviews, and governance routines aligned with PMO practices; contribute to Ralliant technology and architecture forums.