Who You'll Be Working With

As an AWS Data Solution Architect at Capgemini, you will design and lead the delivery of modern data platforms that enable analytics, AI, GenAI, and data driven decision making at scale. You will translate business strategy into robust, governed, and AI ready architectures, taking end to end ownership from vision through to delivery and value realisation

You will be part of the Data Platforms team that is part of the Insights and Data Global Practice that has seen strong growth and continued success across a variety of projects and sectors. Data Platforms is the home of the Data Engineers, Platform Engineers, Solutions Architects and Business Analysts who are focused on driving our customers digital and data transformation journey using the modern cloud platforms. We specialise on using the latest frameworks, reference architectures and technologies using AWS, Azure and GCP along with various data platforms like Databricks and Snowflake

Please Note:

Security Clearance: To be successfully appointed to this role, must be eligible to obtain Security Check (SC)clearance.
To obtain SC clearance, the successful applicant must have resided continuously within the United Kingdom for the last 5 years, along with other criteria and requirements.

Throughout the recruitment process, you will be asked questions about your security clearance eligibility such as, but not limited to, country of residence and nationality.
Some posts are restricted to sole UK Nationals for security reasons; therefore, you may be asked about your citizenship in the application process.

The Focus Of Your Role

As a Solution Architect with an AWS data platform focus, you will be an integral part of our team dedicated to building scalable, secure, and well-governed data platforms. You will leverage your expertise in AWS analytics and data integration services to design, develop, and implement modern data architectures and pipelines that fuel analytics, AI/ML, and data-driven operations.

Design and build high-performance data integration solutions: Use AWS Glue, AWS Step Functions, Amazon EventBridge, and AWS Database Migration Service (DMS) to orchestrate ingestion, transformation, and movement of data across on-premises and cloud sources into Amazon S3 and downstream analytics services.
Design and oversee the delivery of secure lakehouse and warehouse architectures: Implement logical and physical data models, data quality controls, and governance practices using Amazon S3 (data lake), AWS Lake Formation, Amazon Redshift, and Amazon Athena to ensure trusted data.
Ability to design AI/ML-enabled solutions: Enable feature-ready, governed datasets for data science and integrate with Amazon SageMaker (and related AWS AI services) to operationalise models and drive business insights.
Design, monitor and optimise data pipelines and platform performance: Use Amazon CloudWatch, AWS CloudTrail, and service-native monitoring to improve reliability, throughput, cost, and scalability across ingestion, storage, and analytics workloads.
Collaborate with cross-functional teams: Work closely with business analysts, data engineers, data scientists, and platform/DevOps teams to implement secure CI/CD, environment management, and scalable multi-account patterns (e.g., landing zones) for governed delivery.
Stay ahead of the curve: Continuously learn and adapt to the evolving AWS data and analytics landscape, including AWS Glue, Lake Formation, Redshift, Athena, EMR, and related best practices.
Define the platform operating model: Establish AWS multi-account strategies, environment separation (dev/test/prod), naming standards, and guardrails that enable secure self-service while maintaining control and consistency.
Support governance and metadata management: Implement data discovery, classification, lineage, and stewardship practices using AWS Glue Data Catalog, AWS Lake
Formation, and aligned standards for trusted, auditable data products.
Own security architecture for data platforms: Design identity, access, and secrets management (e.g., AWS IAM, IAM Identity Center, KMS, Secrets Manager) and apply network and monitoring controls appropriate for sensitive public sector workloads.
Embed engineering excellence: Define CI/CD and release management for AWS data platforms, including Git-based workflows, automated testing, and repeatable environment provisioning using Infrastructure-as-Code (e.g., AWS CDK, CloudFormation, Terraform, and AWS CodePipeline/CodeBuild).
Drive FinOps and capacity planning: Shape cost governance (tagging, chargeback/showback), monitor usage with AWS Cost Explorer and AWS Budgets, and optimise designs using the AWS Well-Architected Framework and service best practices.
Lead migration and modernisation: Assess legacy estates and design pragmatic roadmaps to modern AWS architectures (including S3-based data lakes and Redshift-based analytics), covering transition planning, delivery governance, and risk management.

What You'll Bring

You will bring deep experience delivering data platforms and data architecture within complex public sector environments, with a strong understanding of government operating models, regulatory obligations, and the need for trusted, mission critical data. You will have a proven ability to design secure, scalable, and well governed data foundations that support analytics, AI, and GenAI while meeting requirements for data protection, sovereignty, transparency, and auditability. You will be comfortable working with senior stakeholders to translate outcomes into pragmatic data and AI architectures, balancing innovation with risk management. You will bring strong leadership and collaboration skills, enabling multi supplier delivery teams to align around shared standards, reuse platforms effectively, and build sustainable data capabilities that deliver long term value for citizens and public services.

Experience:

Minimum 7+ years of experience as a Data Architect, including designing, developing and implementing solutions on AWS data and analytics platforms.
Proven expertise in data integration and analytics platforms on AWS, with strong understanding of data warehousing, dimensional modelling, and lakehouse/data lake concepts.
Experience with AWS cloud platform, including Amazon S3, AWS Lake Formation, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR, and related security, networking, and monitoring services.
Excellent problem-solving and analytical skills and strong communication and teamwork skills.
Passion for data and a thirst for learning; either already an AWS advocate or working towards deep capability across AWS data and analytics services.
Relevant AWS certifications (e.g., AWS Certified Solutions Architect, AWS Certified Data Engineer – Associate (or equivalent), and/or AWS Certified Security – Specialty).
Experience with CI/CD and Infrastructure-as-Code for AWS platforms (e.g., Git-based workflows, AWS CDK/CloudFormation/Terraform, and AWS CodePipeline/CodeBuild).

Additional Information

Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.

If you are successfully offered this position, you will go through a series of pre-employment checks, including identity, nationality (single or dual) or immigration status, employment history going back 3 continuous years, and unspent criminal record check (known as Disclosure and Barring Service)

What we’ll offer you

You will be encouraged to have a positive work-life balance. Our hybrid-first way of working means we embed hybrid working in all that we do and make flexible working arrangements the day-to-day reality for our people. All UK employees are eligible to request flexible working arrangements.

You will be empowered to explore, innovate, and progress. You will benefit from Capgemini’s ‘learning for life’ mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard Manage Mentor, Cybersecurity qualifications and much more.

Why we’re different

At Capgemini, we help organisations across the world become more agile, more competitive, and more successful. Smart, tailored, often ground-breaking technical solutions to complex problems are the norm. But so, too, is a culture that’s as collaborative as it is forward thinking. Working closely with each other, and with our clients, we get under the skin of businesses and to the heart of their goals. You will too.

Capgemini is proud to represent nearly 130 nationalities and its cultural diversity. Our holistic definition of diversity extends beyond gender, gender identity, sexual orientation, disability, ethnicity, race, age, and religion. Capgemini views diversity as everything that makes us who we are as an organization, including our social background, our experiences in life and work, our communication styles and even our personality. These dimensions contribute to the type of diversity we value the most: diversity of thought.