Data Architect

Salary: £33,500 - 47,500 per year

Requirements:

• We require a Bachelors degree in Computer Science, Information Systems, or a related field, or equivalent professional experience; an advanced degree is a plus but not required.
• We are looking for approximately 3-5 years of experience in data architecture, data engineering, or a related data management role.
• We need strong proficiency in data modelling and database design, including ER diagrams and relational schema design.
• We require practical experience with SQL and at least one relational database.
• We expect experience working with NoSQL databases, especially graph databases.
• We are looking for hands-on experience developing data pipelines and integration workflows using ETL/ELT tools or Python/SQL scripting.
• We need experience with batch processing; real-time streaming experience with Kafka or equivalent is a plus.
• We value exposure to semantic data modelling, ontologies, or knowledge graph construction.
• We expect experience with cloud-based data platforms or big data technologies, including data lakes, data warehouses, or distributed computing.
• We require a solid understanding of data governance principles and best practices, including data privacy, data protection, and compliance.
• We value experience implementing data quality checks, defining data standards, and using or setting up metadata management tools.
• We need excellent communication skills and the ability to collaborate in cross-functional teams.
• We value problem-solving aptitude and a willingness to mentor junior data team members.
• Experience working on AI or machine learning projects is a plus.
• Familiarity with data governance or data cataloguing tools such as Collibra, Alation, or Apache Atlas is a strong plus.
• Experience with modern data architecture patterns such as data lakehouse, data mesh, or event-driven/streaming architectures is a plus.
• Relevant industry certifications, such as AWS, Azure, or GCP data engineering certifications or CDMP, are advantageous.
• English proficiency at C1 Advanced level is required.

Responsibilities:

• We design and implement the data architecture needed to support machine learning and AI solutions.
• We define data models, storage patterns, and governance frameworks.
• We ensure that data from various sources is well-organised, accessible, and AI-ready.
• We work closely with data engineers and ML engineers to build robust data pipelines.
• We maintain high data quality for analytics and model development.
• We develop and maintain conceptual, logical, and physical data models.
• We design relational schemas, graph data models for knowledge graphs, and time-series data structures as needed.
• We define and implement data storage and management patterns that optimise retrieval and analytics performance.
• We select or design appropriate storage solutions, including relational databases, NoSQL/graph databases, data warehouses, and data lakes.
• We build and oversee robust ETL/ELT data pipelines to integrate data from multiple sources into centralised platforms.
• We design workflows to collect, transform, and load data into analytics repositories or feature stores.
• We set up stream processing for real-time data when required and automate pipeline orchestration.
• We establish and enforce data governance policies and standards.
• We define practices for data quality, data cleaning, and master data management.
• We set security and privacy controls to protect sensitive information.
• We ensure compliance with relevant data regulations and implement validation rules.
• We implement frameworks for data metadata management and lineage tracking.
• We maintain data catalogues or dictionaries that describe data meaning.
• We work closely with data engineers, ML engineers, and data scientists to ensure the data architecture meets their needs.
• We collaborate on designing data interfaces such as APIs or query endpoints.
• We help shape how data is used for features in machine learning.
• We monitor the performance and scalability of the data infrastructure and tune it as the AI project grows.
• We optimise database queries, indexing, and storage layouts for faster model training and inference data access.
• We plan for scale using cloud capabilities and manage costs effectively.
• We evaluate new technologies and incorporate them to continually improve the architecture.

Technologies:

• AI
• AWS
• Architect
• Azure
• Big Data
• Cloud
• ETL
• GCP
• Support
• Kafka
• Machine Learning
• Model Training
• NoSQL
• Python
• SQL
• Security
• Data Warehouse
• Flow
• RDF
• VR

More:

We are seeking a Senior Data Architect to join our AI project team in London, United Kingdom of Great Britain and Northern Ireland. This role sits within our AI/ML work in the BCM industry and focuses on building AI-ready data architecture for machine learning and analytics. We offer a collaborative environment where you will work closely with data engineers, ML engineers, and data scientists, translating requirements across teams and supporting the path from raw data to AI insights.

last updated 34 week of 2026