Principal Enterprise Data Platform Architect

As the Principal Enterprise Data Platform Architect, you will serve as the technical lead and pillar head for Data Platform Engineering within the Data Excellence & AI Foundations organization. Reporting directly to the Director of Data Excellence & AI Foundations, you will be responsible for defining, architecting, and evolving Avery Dennison's enterprise 10-Layer Data & AI Operating System. In this role, you will lead the technical transition from legacy ETL pipelines toward a modern, high-code Platform Engineering practice grounded in GitOps, Data-as-Code, declarative management, and automated metadata control planes while mentoring and elevating internal engineering talent. Position Location: Remote

Responsibilities

Own the global architecture blueprint and technology decision trees for Avery Dennison's enterprise analytical and AI platforms, architecting the 10-Layer Modern Data Operating System across multi-cloud environments (OCI, GCP, Azure); Architect and deploy the centralized Metadata Control Plane and automated Data Catalog, coordinating schema tracking, lineage graphs, data quality observability, GitOps methodologies, reusable developer toolboxes, and context-as-code for LLM reasoning; Design and govern enterprise AI infrastructure standards, including Vector Databases, Knowledge Graphs, Feature Stores, and RAG pipelines for corporate Gemini LLM solutions and autonomous AI agents with deterministic verification mechanisms; Design and enforce the Universal Security Model incorporating Attribute-Based Access Control (ABAC), fine-grained masking, and Okta/Active Directory identity integration, while implementing SRE-style observability for platform health, latency, query performance, and compute costs; Serve as Pillar Lead for the Data Platform Engineering squad, guiding and mentoring technical talent across pipeline, data, analytics, AI/LLM, DevOps, and APEX engineering while partnering with HR on technical career progression tracks and competency matrices

Requirements

Master's or Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or a related quantitative field; 10+ years in enterprise data architecture, platform engineering, or cloud infrastructure design (including 3+ years leading technical teams in a global enterprise context); Expert technical proficiency in multi-cloud environments (OCI, GCP, Azure), Oracle ADW (23c/26ai), Databricks, and Apache Iceberg or Delta Lake table formats; High-code data engineering mastery in Python, SQL, Apache Airflow, Kafka/Confluent streaming, Change Data Capture (CDC / GoldenGate), Docker, Kubernetes, Terraform, and GitOps CI/CD deployment pipelines (GitHub Actions/GitLab CI); Direct experience architecting enterprise AI/ML infrastructure, including Vector DBs, Knowledge Graphs, Feature Stores, RAG pipelines, and enterprise LLM integrations (Gemini); Strong strategic leadership and communication skills with a proven track record of mentoring technical talent, establishing Universal Security Models (ABAC, RLS, Okta/AD), and presenting complex architectural blueprints to executive sponsors (VP/CIO)

Benefits

Inclusive Healthcare: Access to a large network of medical and behavioral health professionals; 401(k) Retirement Plan: automatic company contribution of 3% of eligible pay plus a matching contribution of 50% on the first 7% of eligible pay contributed; Medical Insurance: healthcare and insurance options for you and your family; Paid Time Off: generous vacation program that varies based upon experience and position