Principal Data Architect - Databricks & AI

The opportunity

We are investing   in the next generation of   our   data and technology capabilities to create more connected, intelligent experiences for customers. Data is central to this ambition. This is an opportunity to define the architecture, standards and delivery patterns for a modern data platform that will enable trusted data use across products and support advanced analytics and AI.

The Principal Data Architect will be the senior technical authority for data architecture within this strategic transformation. The role is architecture-led while   remaining   practically engaged through prototyping, proof-of-concepts, technical   reviews   and the resolution of complex engineering challenges. As the capability grows, the remit may expand to include leadership of a small team .

What you   will do

- 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 that enables secure, scalable use of data across a complex product landscape .

- Establish scalable medallion patterns across  Bronze, Silver and Gold  layers, including ingestion, transformation, storage,  serving  and consumption.

- Design  canonical ,  dimensional  and semantic data models that enable 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,  anonymisation  or equivalent controls for customer data used in AI and analytical workloads.

- Design AI-ready data capabilities, including governed model-data pipelines, vector search and retrieval-augmented generation patterns where relevant.

- Create prototypes and proof-of-concepts, review technical designs and code, guide performance  optimisation , and help 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 customer and product needs into architecture and delivery plans.

- Mentor data engineers and architects and promote reusable platform capabilities and engineering standards.

What you bring

- 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  optimisation  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,  anonymisation ,  tokenisation  or comparable privacy-preserving patterns for sensitive or customer data.

- Strong data-modelling  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. AWS experience is  advantageous  as the platform expands.

- Experience with governance, cataloguing, lineage, quality, metadata, access control and secure multi-tenant or customer-data environments.

- Credibility with hands-on engineers and senior stakeholders, with strong judgement across speed, scale, governance,  cost  and usability.

Valuable  additional  experience

- Production AI/ML or generative-AI data architecture, including RAG, embeddings, vector  search  or  model-data  pipelines.

- Knowledge graphs, ontologies, RDF, linked  data  or advanced semantic technologies.

- Databricks or cloud architecture/ data-engineering  certification.

- Tools such as  dbt , Kafka, Airflow, Terraform, Power BI, Tableau,  Collibra  or Microsoft Purview.

- Architecture across multiple products,  domains  or business units in B2B software, information services,  consulting  or regulated environments.

Why join

This is a rare opportunity to shape a strategically important data foundation from the beginning. You will have the mandate to make high-impact architectural decisions, work on complex technical challenges and influence how trusted data powers better customer experiences, advanced analytics and AI. The role offers meaningful visibility, broad collaboration and the chance to create capabilities that will scale across   an   evolving product landscape.

Our Interview Practices

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.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.