Principal Data Architect

We are seeking a Principal Data Architect with 15+ years of experience architecting, governing, and transforming enterprise-wide data ecosystems. This strategic leadership role involves defining data architecture roadmaps, modernising data platforms, driving cloud transformation, and enabling AI-ready data foundations at scale. The successful candidate will act as a trusted advisor to business and technology leaders, ensuring data, analytics, and AI strategies align with enterprise objectives.

A leading global consulting firm known for combining mathematical rigour with deep data and AI expertise. The organisation partners with enterprises across industries to solve complex analytical and technology challenges at scale. It is recognised for its inclusive, collaborative culture and strong commitment to innovation and employee growth.

Responsibilities

• Define and govern enterprise-wide data architecture strategy aligned with organisational goals and digital transformation initiatives
• Lead the design of scalable, cloud-native data platforms supporting analytics, AI/ML, GenAI, real-time processing, and operational workloads
• Establish architecture standards, reference frameworks, and best practices for data engineering, integration, governance, and security
• Drive enterprise data modernisation, including migration from legacy systems to modern cloud data ecosystems
• Provide architectural leadership for data lakes, lakehouses, data warehouses, and distributed data platforms across AWS, Azure, and GCP
• Govern data quality, lineage, cataloguing, privacy, compliance, and access management frameworks
• Oversee design and optimisation of real-time streaming architectures and evaluate platforms such as Databricks, Snowflake, and BigQuery
• Champion AI-ready data capabilities, including feature stores, semantic layers, vector databases, and GenAI data architectures
• Mentor data architects and senior engineers, and establish architecture review and solution governance frameworks

Requirements

• 15+ years of experience in data architecture, data engineering, data platform engineering, or enterprise architecture, with relevant domain experience
• 8+ years designing and implementing enterprise-scale cloud-based data solutions
• Proven track record of leading large-scale data transformation and modernisation programmes for global enterprises
• Deep expertise across AWS, Azure, and GCP data services, and distributed frameworks such as Spark, Hadoop, Databricks, and Snowflake
• Strong experience with streaming technologies such as Kafka, Event Hubs, Kinesis, and Pub/Sub, and with lakehouse architectures
• Expertise in enterprise data governance, metadata management, data cataloguing, and lineage frameworks
• Knowledge of regulatory compliance requirements such as GDPR, HIPAA, and CCPA, and of secure data platform design
• Experience working directly with executive stakeholders and communicating architectural strategy effectively
• Demonstrated ability to mentor senior technical professionals and lead cross-functional teams

Skills

Enterprise Data Architecture, Cloud Data Platforms (AWS, Azure, GCP), Databricks, Snowflake, Spark, Kafka, Data Governance, Data Modernization, Lakehouse Architecture, Azure Data Factory, Informatica, Talend, Data Fusion, Glue, Synapse, BigQuery, Redshift, Fabric, Event Hubs, Kinesis, Pub/Sub, Spark Streaming, Hadoop, Python, Scala, Java, SQL, MLOps, DataOps, CI/CD, Infrastructure as Code, Vector Databases, Knowledge Graphs, Feature Stores, Metadata Management, Master Data Management, Data Mesh, Data Fabric, GDPR, HIPAA, CCPA