Data Architect

Overview

As a Data Architect at PA Consulting, you will drive data and AI transformations for clients by defining data blueprints and end-to-end architecture. You will design multi-cloud data platforms with ingestion, governance, security, cost-optimisation and observability, while translating business needs into scalable solutions. You’ll lead engineering teams, shape strategic direction, and collaborate across cross-functional squads to deliver secure, high-performance data products. This is an opportunity to influence client outcomes and contribute to a culture that values learning, inclusion and excellence.

Pay / Benefits

• private healthcare for you and family
• 25 days annual leave (+1/2 day Christmas Eve)
• generous company pension
• community and charity initiatives
• annual performance-based bonus
• PA share ownership-Tax efficient benefits (cycle to work, give as you earn)

Responsibilities

• Define data blueprint and architecture for complex programmes
• Architect end-to-end data platforms (ingestion, governance, security, observability, cost-optimisation)
• Translate business needs into scalable data solutions for clients
• Operate at strategic level and lead teams to end-to-end delivery
• Bid leadership and business growth through opportunity identification
• Mentor and develop newer team members; share thought leadership
• Set direction for teams and foster an inclusive, high-standard environment
• Collaborate with engineering teams as a core SME to establish practical architecture
• Work in agile, cross-functional, client-facing settings with hybrid on-site/work arrangements

Key requirements

• Hands-on data background with experience leading engineering teams
• Clear understanding of data architecture and delivery methodologies
• Experience across data domain with awareness of AI impact in solutions
• Commitment to continuous professional development
• Strong problem-solving and analytical thinking
• Ability to collaborate with multiple stakeholders in fast-paced environments
• Certifications in relevant methodologies and cloud technologies are advantageous
• Experience with multiple cloud platforms (AWS, Azure, GCP) and data platforms (Databricks, Snowflake) is desirable

• collaboration
• stakeholder management
• analytical thinking
• Multi-cloud data platforms (AWS, Azure, GCP)
• Data warehousing and data lake architectures
• Data ingestion and integration technologies

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