Associate Director, Solutions Architect - Data, Analytics & AI​/ML Platforms; Remote

What You Will Do

The Associate Director, Solutions Architect for Data, Analytics & AI/ML Platforms is a senior technical leader responsible for defining the end‑to‑end architecture of enterprise data platforms, advanced analytics solutions, and AI/ML capabilities. This role drives platform modernization across cloud, Lakehouse, and AI ecosystems. The leader combines deep technical expertise, enterprise systems thinking, and strong communication skills to guide development teams, influence business strategy, and ensure seamless integration across platforms such as Databricks, Azure, AWS, SAP S/4, and emerging AI toolsets.

The role functions as a key bridge between business, product, architecture, and Digital Technology organizations. Success requires thought leadership, architectural rigor, strong stakeholder engagement, and the ability to design scalable, secure, and high‑performing data solutions across the enterprise.

• Enterprise Architecture & Strategy:
  • Define the long‑term architecture for data, analytics, and AI/ML platforms in alignment with enterprise digital strategy.
  • Develop reference architectures, design patterns, and platform standards for cloud, Lakehouse, and AI ecosystems.
  • Define and lead technology proof of concepts to ensure feasibility of architecture solutions.
  • Provide strong thought leadership in pursuit of modern architecture principles and technology modernization.
  • Evaluate emerging technologies and provide strategic recommendations (AI, knowledge graphs, real‑time streaming, ML Ops, etc.).
  • Drive continuous technology transformation to minimize technical debt.
• Solution & Platform Architecture:
  • Architect end‑to‑end solutions spanning ingestion, transformation, governance, analytics, and ML operationalization.
  • Lead architectural design for platforms such as Databricks, Snowflake, Azure Data Services, SAP S/4 connectors, and enterprise knowledge graph/ontology platforms.
  • Define patterns for real‑time streaming, data virtualization, metadata frameworks, and multi‑cloud integration.
  • Ensure platform scalability, performance, redundancy, cost optimization, and security.
• Governance, Security & Compliance:
  • Collaborate with Cybersecurity and Data Governance teams to enforce data privacy, lineage, cataloging, and access control standards.
  • Ensure compliance with government regulations, export control, and enterprise security policies.
• Leadership & Stakeholder Management:
  • Provide architectural leadership across cross‑functional engineering teams and strategic programs.
  • Serve as a trusted advisor to business executives, product owners, and technical stakeholders.
  • Mentor and guide data engineers, architects, and analytics practitioners across the organization.
  • Lead architecture governance forums and design reviews for major programs.

• Bachelor’s degree in Computer Science, Engineering, Data Science or related technical field and 12+ years of applicable work experience; OR an Advanced degree in Computer Science, Engineering, Data Science or related technical field and 10+ years of applicable work experience.
• U.S. citizenship is required, as only U.S. citizens are authorized to access information under this program/contract.
• 10+ years of experience in data engineering, data architecture, analytics, AI/ML, or related technical domains.
• 5+ years architecting cloud‑native data platforms (Azure, AWS, or GCP).
• Deep experience with Databricks, Lakehouse architectures, and modern ELT/ETL tooling.
• Strong understanding of distributed systems, real‑time data streaming, data governance, and API/Integration architectures.
• Demonstrated ability to design and implement enterprise‑scale data architecture solutions.
• Strong stakeholder management, communication, and executive engagement skills.

• Experience with SAP S/4
  
  HANA integrations, manufacturing data, or aerospace & defense environments.
• Hands‑on knowledge of AI/ML frameworks (MLflow, Feature Stores, RAG, vector databases).
• Experience with knowledge graph / ontology platforms (e.g., Kobai, Neo4j, Databricks Graph technologies).
• Experience leading teams in Agile delivery environments.
• Proven ability to drive…