Data Architect

Location: West Midlands (Hybrid working model)

Duration: 6 Months

IR35: Inside IR35

£(Apply online only)p/d

Start: ASAP

Xpertise are working with a business based in the Midlands to support on a major transformation to become a more risk-based, data-driven organisation. As part of this strategic move, they're transitioning from Idea to Discovery phase and need a Data Architect to help shape the future of data governance, predictive analytics, and regulatory insight.

The Opportunity:

This is more than a technical role – it's about building the foundations of a modern data estate. You'll be the senior voice on all things data architecture, tasked with creating a Data Catalogue, implementing data governance tooling, and laying the strategic and technical groundwork for a future ML Ops pipeline.

You'll work closely with an Enterprise Architect and key stakeholders to create structure, define workstreams, and bring external data sources into the fold to support predictive regulatory analytics.

Key Responsibilities:

Define and implement a scalable data architecture that aligns with regulatory and business goals.

Lead the implementation of a Data Catalogue and Governance Suite (e.g., Collibra, Alation, Informatica).

Design and maintain data models, lineage, and metadata standards.

Collaborate with business and enterprise stakeholders to establish data ownership and governance.

Enable a Data-Driven Operating Model (DDOM) – embedding data literacy and strategy across the organisation.

Support the foundations of an ML Ops environment for predictive analytics and behavioural insight.

Liaise confidently across all levels – from technical teams to senior leadership.

About You:

Proven experience as a Data Architect within a regulated environment (e.g., financial services, government, healthcare).

Skilled in both strategic planning and hands-on data modelling.

Familiarity with modern data stacks (Snowflake, Databricks, dbt) and cloud platforms (AWS, Azure, GCP).

Strong communicator with the ability to lead discussions, shape roadmaps, and influence outcomes.

Comfortable working in ambiguous environments and guiding organisations through early-stage discovery.

Desirable:

Certifications in Data Architecture, Governance, or Cloud.

Experience working with or implementing DDOM frameworks.

Understanding of ML Ops tools (e.g., MLflow, SageMaker, Kubeflow) and data privacy regulations (GDPR, CCPA)