Senior Technical Consultant - Data Architect in London

Working Structure: Hybrid (Regular visits to client site)

The role: As a Data Architect at CACI Information Intelligence Group, you will join a community of dedicated engineers delivering cutting-edge data solutions for our public sector customers across Central Government, Defence, National Security, Critical National Infrastructure and Law Enforcement.

This role is focused on architecting and delivering modern cloud data platforms, with particular emphasis on Snowflake and/or Databricks. You will work directly with customers to design, assess, optimise, and modernise enterprise data ecosystems, ensuring they are scalable, secure, cost-effective and aligned with industry best practices.

You will act as a trusted technical advisor, leading the architecture of data platforms that enable advanced analytics, AI/ML workloads, data sharing, and operational reporting. Working across the full project lifecycle, you will define target-state architectures, data models, governance frameworks, and integration patterns, whilst ensuring alignment with security, compliance and operational requirements.

As a Data Architect, continuous professional development is a key part of your growth. You will be expected to maintain deep expertise in modern data technologies, particularly Snowflake and Databricks, and help shape both customer and internal data strategies.

Clearance Requirements: Due to the industries this role will be associated with, we require the successful candidate to be eligible for security clearance. To qualify for this, you must be a British Citizen and have lived permanently in the UK for the last 5 years.

Responsibilities:

• Platform Architecture Leadership: Act as the lead architect for Snowflake and Databricks-based data platforms, defining architecture roadmaps and ensuring alignment to customer business objectives.
• Snowflake Architecture: Design and optimise Snowflake environments, including data sharing, secure data access, data warehouse design, performance tuning, governance, and cost optimisation.
• Databricks Architecture: Design and implement Databricks lakehouse architectures, supporting large-scale data engineering, streaming, analytics, AI, and machine learning workloads.
• Assessment & Modernisation: Evaluate existing data estates and develop migration strategies to modern cloud data platforms, including Snowflake and Databricks.
• Data Modelling & Design: Develop enterprise data models, Lakehouse architectures, medallion data architectures, and data platform standards.
• Integration & Engineering: Define scalable patterns for data ingestion, transformation, orchestration, and integration across cloud and hybrid environments.
• Collaboration: Partner with data engineers, analysts, cloud architects, security teams, and customer stakeholders to deliver high-quality data solutions.
• Governance & Security: Establish and enforce governance frameworks covering data quality, lineage, metadata management, access controls, and regulatory compliance.
• Documentation: Produce and maintain architecture artefacts, standards, patterns, and technical documentation.
• Future Technology: Guide customers on emerging technologies including AI, ML, GenAI, and advanced analytics leveraging Snowflake and Databricks capabilities.
• Cloud Experience: Proven experience in multi-cloud architecture across AWS and Azure, designing and integrating modern data solutions with cloud-native services to deliver scalable, secure, and business-aligned outcomes.

Person & Specification:

Knowledge:

• Strong understanding of modern data platform architecture, including Snowflake Data Cloud and/or Databricks Lakehouse Platform.
• Strong knowledge of cloud-native data architectures across Azure and AWS.
• Strong understanding of data governance, security, metadata management, and data lifecycle management.
• Understanding of AI/ML data requirements and modern analytics platforms.
• Knowledge of big data processing frameworks and distributed computing concepts.
• Aware of emerging capabilities in data sharing, data products, and data mesh architectures.

Experience:

• Proven experience as a Data Architect delivering enterprise-scale cloud data platforms.
• Significant hands-on experience designing and implementing solutions using Snowflake and/or Databricks.
• Experience architecting lakehouse, data warehouse, and hybrid analytical platforms.
• Experience defining migration strategies from legacy data platforms to Snowflake or Databricks.
• Proven expertise in data modelling, interoperability standards, and enterprise integration patterns.
• Experience implementing data governance, lineage, security, and compliance controls within modern data platforms.
• Experience leading architecture decisions across complex stakeholder environments.
• Strong understanding of data pipelines, ETL/ELT frameworks, orchestration tooling, and data engineering best practices.
• Familiarity with technologies such as Spark, Python, SQL, Delta Lake, Unity Catalog, dbt, Azure Data Factory, Airflow, Kafka, or equivalent tooling.
• Relevant certifications such as Snowflake SnowPro, Databricks Certified Data Engineer, or cloud platform certifications would be an advantage.

Skills:

• Strong communication, consulting, and stakeholder management skills.
• Ability to influence senior technical and non-technical audiences on data platform strategy.
• Experienced in developing design documentation and option papers, guiding solutions through formal governance processes, and presenting proposals to architecture and governance boards (including TDAs) to secure approval and alignment.
• Strong analytical and problem-solving capabilities.
• Ability to translate business requirements into scalable Snowflake and Databricks architectural solutions.
• Passion for promoting data as a strategic asset and enabling data-driven decision making.
• Ability to mentor engineers and architects while contributing to technical leadership within delivery teams.
• Experience balancing performance, security, scalability, and cost optimisation within cloud data platforms.