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About the Role

This role is for a Principal Data Architect who will be the senior technical authority for data architecture within a strategic transformation. The position involves defining the architecture, standards, and delivery patterns for a modern data platform to enable trusted data use, advanced analytics, and AI. The role is architecture-led but practically engaged through prototyping, proof-of-concepts, technical reviews, and resolving complex engineering challenges. There is potential for leadership of a small team as the capability grows.

Responsibilities

Define and own the target data architecture, standards, reference patterns, and technical roadmap for a strategic enterprise data capability.
Design a modern Databricks lakehouse foundation for secure, scalable data use across a complex product landscape.
Establish scalable medallion patterns (Bronze, Silver, Gold) including ingestion, transformation, storage, serving, and consumption.
Design canonical, dimensional, and semantic data models for consistent exchange, interoperability, and reuse across product domains.
Architect secure data integration using batch, streaming, APIs, change data capture, and event-driven patterns.
Design privacy-preserving data capabilities, including data masking, anonymization, or equivalent controls for customer data.
Design AI-ready data capabilities, including governed model-data pipelines, vector search, and retrieval-augmented generation patterns.
Create prototypes and proof-of-concepts, review technical designs and code, guide performance optimization, and resolve complex technical issues.
Build production-ready solutions with strong governance, lineage, quality, observability, security, reliability, and cost control.
Partner with product, engineering, AI, security, platform, and business leaders to translate needs into architecture and delivery plans.
Mentor data engineers and architects, promoting reusable platform capabilities and engineering standards.

Requirements

Significant experience as a Data Architect, Lead Data Architect, Principal Data Engineer, or comparable senior technical leader.
Advanced, hands-on Databricks experience in production environments, including lakehouse architecture, Delta Lake, and relevant governance, workflow, SQL, and optimization capabilities.
Proven ownership of modern data platforms or data products from architecture through production delivery and operation.
Strong experience in data privacy and security, including data masking, anonymization, tokenization, or comparable privacy-preserving patterns for sensitive or customer data.
Strong data-modeling expertise across conceptual, logical, physical, dimensional, and canonical models.
Experience with batch and real-time integration, including APIs, CDC, streaming, or event-driven pipelines.
A strong data-engineering or software-development foundation using Python, SQL, Scala, Java, and/or Spark.
Deep experience with Azure data services.
Experience with governance, cataloging, lineage, quality, metadata, access control, and secure multi-tenant or customer-data environments.
Credibility with hands-on engineers and senior stakeholders, with strong judgment across speed, scale, governance, cost, and usability.

Skills

Databricks
Lakehouse architecture
Delta Lake
Data governance
Data workflow
SQL
Performance optimization
Data privacy
Data security
Data masking
Anonymization
Tokenization
Data modeling
Dimensional modeling
Canonical modeling
Batch integration
Real-time integration
APIs
CDC
Streaming
Event-driven pipelines
Python
Scala
Java
Spark
Azure data services
AWS
Data cataloging
Data lineage
Data quality
Metadata management
Access control
Multi-tenant environments
Customer data environments
AI/ML data architecture
RAG
Embeddings
Vector search
Model-data pipelines
Knowledge graphs
Ontologies
RDF
Linked data
Semantic technologies
dbt
Kafka
Airflow
Terraform
Power BI
Tableau
Collibra
Microsoft Purview

Location

Onsite at a Wolters Kluwer office

Work Type

Onsite

Experience Level

Principal
Senior technical leader
Advanced

Education Level

Databricks certification
Cloud architecture certification
Data-engineering certification

About the Company

Investing in the next generation of data and technology capabilities to create more connected, intelligent experiences for customers.
Data is central to this ambition.

Equal Opportunity

To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you—not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.