Principal Enterprise Data Platform Architect
Avery Dennison · Mentor, Ohio
What the posting says
Each fact was read from this posting and checked:Statedin the posting, quotedConflictsposted two ways, both shownNot mentionedwe looked; it is not there
- PayStated
- $141,825–$211,792 a year
- Employment typeStated
- Full time
- Work arrangementStated
- Remote OK
- ExperienceStated
- 10+ years
- EducationStated
- ['bachelor degree', 'postgraduate degree']
Not mentioned in this posting
We read the whole posting. These are not in it. Not a no: ask the recruiter, in your own words.
- ShiftNot mentioned
- The posting does not say
- Visa sponsorshipNot mentioned
- The posting does not say
Requirements, each with its sentence from the posting
These are the employer’s words. The index does not judge whether you meet them.
- Master's or Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or related fieldrequired
Master's or Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or a related quantitative field
from the posting - Enterprise data architecturerequired
10+ years in enterprise data architecture, platform engineering, or cloud infrastructure design
from the posting - Leading technical teams in global enterprise contextrequired
3+ years leading technical teams in a global enterprise context
from the posting - Multi-cloud environments (OCI, GCP, Azure)required
Expert technical proficiency in multi-cloud environments (OCI, GCP, Azure)
from the posting - Oracle ADW (23c/26ai)required
Expert technical proficiency in multi-cloud environments (OCI, GCP, Azure), Oracle ADW (23c/26ai)
from the posting - Databricksrequired
Expert technical proficiency in multi-cloud environments (OCI, GCP, Azure), Oracle ADW (23c/26ai), Databricks
from the posting - Apache Iceberg or Delta Lake table formatsrequired
Apache Iceberg or Delta Lake table formats
from the posting - Pythonrequired
High-code data engineering mastery in Python, SQL, Apache Airflow
from the posting - SQLrequired
High-code data engineering mastery in Python, SQL, Apache Airflow
from the posting - Apache Airflowrequired
High-code data engineering mastery in Python, SQL, Apache Airflow
from the posting - Kafka/Confluent streamingrequired
Kafka/Confluent streaming, Change Data Capture (CDC / GoldenGate)
from the posting - Change Data Capture (CDC/GoldenGate)required
Kafka/Confluent streaming, Change Data Capture (CDC / GoldenGate)
from the posting - Dockerrequired
Docker, Kubernetes, Terraform, and GitOps CI/CD deployment pipelines
from the posting - Kubernetesrequired
Docker, Kubernetes, Terraform, and GitOps CI/CD deployment pipelines
from the posting - Terraformrequired
Docker, Kubernetes, Terraform, and GitOps CI/CD deployment pipelines
from the posting - GitOps CI/CD deployment pipelinesrequired
GitOps CI/CD deployment pipelines (GitHub Actions/GitLab CI)
from the posting - Enterprise AI/ML infrastructurerequired
Direct experience architecting enterprise AI/ML infrastructure
from the posting - Vector Databasesrequired
Vector DBs, Knowledge Graphs, Feature Stores, RAG pipelines
from the posting - RAG pipelinesrequired
Vector DBs, Knowledge Graphs, Feature Stores, RAG pipelines
from the posting - Strategic leadership and mentoringrequired
Strong strategic leadership and communication skills with a proven track record of mentoring technical talent
from the posting
Read the full posting as the employer wrote it
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, Okta/AD), and presenting complex architectural blueprints to executive sponsors (VP/CIO).
Additional Information
Pay Transparency
The salary range for this position is $141,825 - $211,792 / year.
The hiring base salary range above represents what Avery Dennison reasonably expects to pay for this position as of the date of this posting. Actual salaries will vary within the range, and in some circumstances may be above or below the range, based on various factors including but not limited to a candidate’s relevant skills, experience, education and training, and location, as well as the job scope and complexity, responsibilities, and regular and/or necessary travel required for the position, which may change depending on the candidate pool. Avery Dennison reserves the right to modify this information at any time, subject to applicable law.
Equal Opportunity Employer
Avery Dennison is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veteran status, or any other protected status.
Reasonable Accommodations Notice
If you require accommodations to view or apply for a job, alternative methods are available to submit an application. Please contact (440) 534-6000 or NA.TA.Operations@averydennison.com to discuss reasonable accommodations.
Identity Verification Notice
To maintain the integrity of our hiring process and protect our candidates from identity fraud, we require video and/or in-person interviews. As part of this verification, we may also ask you to take a brief photo. This image is used exclusively to ensure identity consistency and will be permanently deleted once the hiring process concludes.
Pre-employment Screening Notice
As part of our commitment to maintaining a safe and productive work environment, Avery Dennison requires all final candidates to successfully complete a comprehensive background check and a drug screening. These checks are conducted post-offer and are a condition of employment. All results will be considered in accordance with applicable local, state, and federal laws.
The posting text is reproduced as the employer wrote it; the index adds nothing to it.