Data Architect in Warwick

Work Location: Warwick

Mode of Working (Hybrid / Office-based): Hybrid

If Hybrid, how many days are required in office? 3 days in week

Role Overview

The Principal Data Architect is responsible for defining enterprise-grade data architecture and solution designs for data products across the business. The role ensures alignment with broader solution architecture, enterprise standards, and portfolio prioritisation while supporting the full lifecycle of data products - from concept through delivery and ongoing optimisation. This role plays a pivotal part in delivering the organisation's data strategy by enabling high-quality, secure, scalable, and interoperable data platforms that support analytics, reporting, and advanced data science use cases. The Principal Data Architect ensures data solutions deliver measurable value while meeting performance, cost, security, sustainability, and regulatory requirements through agile delivery methods.

Primary Responsibilities

• Data Architecture

• Owns and defines end-to-end data architecture for complex, enterprise-scale data initiatives.
• Designs and reviews high-level and detailed solution architectures, including logical and physical data models.
• Ensures architectural solutions comply with enterprise standards, governance, security, and regulatory requirements.
• Works closely with IT, business stakeholders, and enterprise architecture teams to identify requirements, pain points, and optimal solutions.
• Develops and maintains architectural standards, patterns, guardrails, and best practices for data integration and platforms.
• Builds stakeholder confidence by ensuring data quality, lineage, and trustworthiness for decision-making.

• Leads the design, build, operationalisation, security, and monitoring of data pipelines and data stores.
• Ensures solutions balance functional and non-functional requirements such as performance, resilience, cost, and scalability.
• Oversees adherence to data standards, architectures, and security controls.
• Contributes to organisational policies, standards, and guidelines for data engineering practices.

• Leads the selection and adoption of data visualisation approaches and tools (e.g., Power BI, Streamlit, React).
• Defines the purpose, scope, and parameters for data visualisations aligned to business needs.
• Ensures effective communication of insights using appropriate textual, numerical, and graphical techniques.
• Advises stakeholders on the appropriate use of data visualisation to support decision-making.

• Supports all stages of data science and analytics solution development.
• Identifies and evaluates appropriate data sources to support predictive and analytical use cases.
• Advocates standards and best practices for developing, evaluating, deploying, and monitoring analytics, ML, and AI solutions.

• Advises on financial planning, budgeting, and cost optimisation for data platforms and solutions.
• Develops financial forecasts and monitors expenditure against agreed tolerances.
• Analyses variances and provides recommendations to optimise use of available budgets.

• Identifies stakeholder communication and engagement needs.
• Acts as a trusted advisor and single point of contact for data architecture topics.
• Facilitates open communication and informed decision-making across technical and business stakeholders.
• Translates complex technical concepts into clear business outcomes.

• Leads scoping, requirements definition, prioritisation, and change management for large and complex initiatives.
• Applies appropriate predictive or agile delivery methods as required.
• Negotiates priorities and resolves conflicts across diverse stakeholder groups.
• Establishes and maintains requirements baselines and governance processes.

• Promotes adoption of approved methods, tools, and standards across programmes and teams.
• Evaluates, selects, and implements appropriate tools aligned to organisational policies.
• Reviews benefits and effectiveness of tools and recommends continuous improvements.

• Performance and Delivery

• Supports the Data Product Manager in driving high-performance delivery across data product teams.
• Leads Agile/SAFe ceremonies to ensure prioritised and timely delivery.
• Supports definition of standards, tooling, and ways of working.

• Encourages inclusive, healthy, and motivating working practices.
• Provides guidance on career development and long-term professional growth.
• Mentors and coaches team members, fostering a strong data culture.

Your Profile

Essential Skills / Knowledge / Experience

• Extensive Knowledge

• Cloud data platforms: Microsoft Fabric, Snowflake, Azure, Databricks
• Data integration, ETL/ELT, CDC, streaming, APIs, and messaging
• Data modelling (relational, dimensional, NoSQL)
• Data governance, security, privacy, and regulatory compliance
• Power BI, Azure ML, ML/AI, Generative and Agentic AI

• End-to-end implementation of cloud data platforms
• Advanced Snowflake capabilities and cost optimisation
• Complex data migrations from enterprise source systems
• Data security, RBAC, access controls, and compliance frameworks (SoX, GDPR)
• Troubleshooting complex data pipeline and platform issues

Qualifications

Essential

• Significant professional experience in data architecture, data engineering, or data management disciplines

Desirable

• Bachelor's or Master's degree in Computer Science, Data Management, Statistics, Applied Mathematics, or related field

Job Dimensions

• Supports leadership of teams of 6-10 (no direct line management)
• Budget responsibility: indirect influence up to £100m

Leadership Qualities & Business Skills

• Operates with high autonomy and accountability
• Influences senior stakeholders and cross-functional teams
• Leads complex, high-impact initiatives
• Demonstrates strong communication, collaboration, and mentoring skills
• Proactively embeds security, risk management, and ethical practices
• Maintains strong awareness of industry trends and emerging technologies