DataOps Engineer

Location: Newcastle upon Tyne

# Data Ops Engineer Birmingham, Bristol, Newcastle Bank House, Manchester, London Apply for this job
* Permanent* Experienced Professionals
* Architecture* -##
** Who You'll Be Working With
** As a Data Ops 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  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, Dev Ops 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 Data Ops Engineer, you will partner closely with engineering and delivery teams to standardise ways of working, improve data application reliability, and enable safe, repeatable releases.
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* 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 Data Ops Engineer, you will develop and deliver secure, automated and operational solutions across a variety of public sector client systems. You will provide hands-on technical expertise to architect and deliver Data Ops capabilities, with a focus on delivering data applications in an automated approach. You will also implement and manage comprehensive monitoring and observability solutions to ensure data quality across the entire data flow, including supporting delivery in air-gapped and other restricted environments.
* Delivering data applications in an automated and continuous fashion.
* Utilising tools like Airflow for orchestration and automating data pipeline deployments using Dev Ops tools and techniques (Docker, Containers, Terraform, Kubernetes)
* Building data pipelines using both cloud-native and open-source data tools to deliver self-contained data processing applications.
* Understanding of data architecture principles and applying this to your delivery work.
* To be comfortable working in air-gapped development environments and deploying in classified environments.##
** What You'll Bring
** You will bring strong Data Ops experience delivering secure and automated delivery capabilities in complex, regulated environments. A key differentiator in this role is your ability to focus on the application of containerisation within a data context, rather than the low-level management of the container platform itself. 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 required:
*** Data Ops* Proficiency in data pipeline orchestration tools
* Containerisation (Docker, EKS, AKS, Kubernetes)
* Proficiency in CI/CD principles and tools
* Familiarity with open-source data tools (e.g., Spark, Kafka, PostgreSQL)
* Infrastructure as Code (Terraform, Ansible)
* Air-gapped development
* Automation* Client / stakeholder management
* Public sector domain understanding
* Technical architecture
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* Experience:

*** You will have significant experience as a Data Ops Engineer delivering Data Ops solutions in public sector or similarly regulated environments.
* Developing, orchestrating and maintaining data pipelines using tools like Airflow, Prefect, or Dagster.
* Containerising data applications using Docker and deploying them to Container Platforms (EKS, AKS and Kubernetes).
* Implementing CI/CD pipelines for data applications.
* Monitoring and troubleshooting data pipelines and applications.
* Working with Infrastructure as Code (IaC) tools (e.g., Terraform, Ansible) to provision and manage data infrastructure within pre-existing platforms.
* Optimising data processing for performance and scalability.
* Any relevant certifications are beneficial (e.g. Kubernetes, cloud platform, Data Ops).
* Experience 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…