Who You'll Be Working With
As a DataOps Engineer at Capgemini, you will help teams build, run, and continuously improve modern data platforms so they are reliable, secure, and easy to change. You will work across engineering and operations to automate delivery, improve data pipeline observability, and embed good governance so analytics and AI workloads can run at scale.
You will be part of the Data Platforms team that sits within the Insights and Data Global Practice. Data Platforms is home to Data Engineers, Platform Engineers, DataOps Engineers, and Solution Architects who help our clients deliver and operate cloud data platforms on AWS, Azure and GCP, including technologies such as Databricks and Snowflake. As a DataOps Engineer, you will partner closely with engineering and delivery teams to standardise ways of working, improve platform reliability, and enable safe, repeatable releases.
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 Senior DevOps Engineer, you will develop and deliver secure, automated delivery and operational solutions across a variety of public sector client systems. You will provide hands‑on technical expertise to architect and deliver DevSecOps capabilities, including CI/CD, containerisation, automation and secure‑by‑design practices. You will also give technical direction for MLOps solutions across classification boundaries and, where applicable, international partner environments, including supporting delivery in air‑gapped and other restricted environments.
Responsibilities
* Develop and deliver technical solutions across a variety of public sector client systems to solve complex operational and delivery challenges.
* Provide technical expertise to architect and deliver DevSecOps solutions.
* Give technical direction for MLOps solutions in regulated environments across classification boundaries and, where applicable, international partner boundaries.
* Develop CI/CD workflows incorporating MLOps tools to enable ML environments for data scientists.
* Containerise solutions using Docker and Kubernetes, including packaging artefacts, security scanning, assurance, and deployment into multiple systems.
* Create modular DevSecOps solutions that support multi‑organisation collaboration and are usable by international colleagues where required.
* Be comfortable with air‑gapped development and deployment in classified environments.
What You'll Bring
You will bring strong Senior DevOps (DevSecOps) experience delivering secure and automated delivery capabilities in complex, regulated environments. You will be comfortable translating client needs into practical technical designs and then building and operating them, with a focus on repeatability, assurance and continuous improvement. You will communicate clearly with both technical and non-technical stakeholders and be confident providing technical direction.
Key Skills
* DevSecOps
* CI/CD (GitLab)
* Containerisation (Docker, Kubernetes)
* YAML, Bash, Python
* Linux
* Air‑gapped development
* MLOps
* Automation
* Client / stakeholder management
* Public sector domain understanding
* Technical architecture
Experience
* Significant experience as a Senior DevOps Engineer delivering DevSecOps solutions in public sector or similarly regulated environments.
* Hands‑on experience designing and building CI/CD pipelines in GitLab, including promotion across environments and integrating security/assurance controls.
* Strong containerisation experience with Docker and Kubernetes, including packaging artefacts, image hardening/scanning, and deploying to multiple target environments.
* Proficiency in YAML and scripting (Bash, Python) and strong Linux fundamentals for building automation and troubleshooting complex systems.
* Experience delivering MLOps capabilities (e.g., model packaging, deployment patterns, and lifecycle controls) and supporting data science teams to run ML workloads.
* Relevant certifications are beneficial (e.g., GitLab, Kubernetes, cloud platform, DevOps, or security‑focused certifications).
* Comfortable delivering in restricted/air‑gapped and classified environments, and confident engaging clients and stakeholders while contributing to technical architecture and design decisions.
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.
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