Principal Enterprise Data Platform Architect

Company Description

Why join Avery Dennison

We are a global materials science and digital identification solutions company with locations in over 50 countries, and approximately 35,000 employees worldwide. As a science and innovation company, we believe that diverse teams are stronger teams. We are committed to fostering a culture of curiosity and courage, where you can grow your career with a company that has innovation in its DNA. Founded on creating real-world impact to enable a better future, we strive to provide an open, collaborative culture where diversity of thought is encouraged and respected. Hear from our employees about what it's like working at Avery Dennison. Learn more at www.averydennison.com.

Benefits

At Avery Dennison, some of the great benefits we provide are:

• Inclusive Healthcare: Access to our large network of medical and behavioral health professionals.

• 401(k) Retirement Plan: Avery Dennison supports your retirement readiness financially through company contributions to the 401(k) Plan. You receive an automatic contribution of 3% of eligible pay (even if you contribute $0) plus a matching contribution of 50% on the first 7% of eligible pay you contribute.

• Medical Insurance: Avery Dennison offers healthcare and insurance options to support you and your family based on your personal needs.

• Paid Time Off: We offer a generous vacation program that varies based upon your experience and position within Avery Dennison.

Job Description

About the role

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.

Key Responsibilities

Position Location: Remote

• 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.

Qualifications

Qualifications

• Master’s or Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or a related quantitative field with 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, Ok