Senior Data Platform Engineer

• Design, develop, test and deploy data platform services and components. • Build and maintain platform capabilities supporting batch and real-time data workloads. • Develop and operate distributed data services using Kafka, Kinesis, Spark, Flink or equivalent technologies. • Build and maintain cloud-native data platform capabilities using AWS and/or Azure. • Support data ingestion, processing, storage and integration across multiple systems. • Develop and maintain data models, schemas and platform data structures. • Support schema evolution, data quality and data integrity across distributed platforms. • Integrate data platforms with relational and NoSQL databases. • Develop automated testing and validation for platform services and data processing components. • Implement and maintain CI/CD pipelines for data platform workloads. • Use Infrastructure as Code to create repeatable and maintainable environments. • Support Docker and Kubernetes-based platform environments. • Monitor platform services and investigate failures, performance issues and operational problems. • Participate in incident investigation and root cause analysis. • Support platform performance, scalability, resilience and availability improvements. • Contribute to platform security, governance and operational readiness. • Work closely with Software Engineers, Data Engineers, DevOps and Architects. • Participate in technical design discussions, code reviews and engineering standards. • Contribute to continuous improvement of platform engineering practices.

You are a hands-on Data Platform Engineer who enjoys building and operating the infrastructure and services that make modern data platforms work reliably in production. You are comfortable working across cloud platforms, streaming, distributed systems, data processing, Infrastructure as Code and containerisation. You understand that effective data platforms need to be secure, scalable, observable, resilient and maintainable, not simply capable of processing data. You take ownership of your work, enjoy solving complex technical problems and work well with engineers across different disciplines. You are pragmatic, technically curious and focused on delivering reliable platform capabilities that create measurable value for clients. Experience working within public sector, utilities or other complex and regulated environments would be highly advantageous.

Aker Systems was founded in 2017 by a team of experienced technology professionals who recognised an opportunity to provide highly secure enterprise data platforms to large organisations. We build and operate ground-breaking, ultra-secure, high performance, cloud-based data infrastructure for the enterprise. Our proprietary technology solutions drive performance and reduce costs while helping our clients to improve the management and sharing of data across their organisations. In 2024, Aker Systems won the Breakthrough Culture Awards highlighting growth companies putting culture first. In 2020 Aker Systems was recognised as a ‘One to Watch’ on the Sunday Times Tech Track. The Company was also recognised at the Thames Valley Tech Awards 2020; winning the Thames Valley Tech Company of the year, the Emerging Tech Company and High Growth Tech Business categories. We encourage people of all different backgrounds and identities to apply. We are committed to maintaining an inclusive, and supportive place for you to do your very best work. Due to the nature of the project, UK Government Security Check (SC) clearance is required. We are looking for a Senior Data Platform Engineer to design, build and operate secure, scalable and reliable data platform capabilities across client delivery projects in the public sector and utilities. You will work closely with Data Engineers, Software Engineers, Architects, DevOps Engineers and client stakeholders to develop and maintain cloud-native data platforms supporting batch, real-time streaming, analytical and operational workloads. This is a hands-on engineering role focused on building reliable platform services, automating infrastructure and deployments, supporting production environments and contributing to technical design decisions. Strong experience with cloud platforms, distributed systems and real-time streaming technologies is highly desirable. Key Responsibilities • Design, develop, test and deploy data platform services and components. • Build and maintain platform capabilities supporting batch and real-time data workloads. • Develop and operate distributed data services using Kafka, Kinesis, Spark, Flink or equivalent technologies. • Build and maintain cloud-native data platform capabilities using AWS and/or Azure. • Support data ingestion, processing, storage and integration across multiple systems. • Develop and maintain data models, schemas and platform data structures. • Support schema evolution, data quality and data integrity across distributed platforms. • Integrate data platforms with relational and NoSQL databases. • Develop automated testing and validation for platform services and data processing components. • Implement and maintain CI/CD pipelines for data platform workloads. • Use Infrastructure as Code to create repeatable and maintainable environments. • Support Docker and Kubernetes-based platform environments. • Monitor platform services and investigate failures, performance issues and operational problems. • Participate in incident investigation and root cause analysis. • Support platform performance, scalability, resilience and availability improvements. • Contribute to platform security, governance and operational readiness. • Work closely with Software Engineers, Data Engineers, DevOps and Architects. • Participate in technical design discussions, code reviews and engineering standards. • Contribute to continuous improvement of platform engineering practices. Essential Technical Skills & Experience • Strong commercial experience as a Senior Data Platform Engineer, Senior Data Engineer, Platform Engineer, Software Engineer or similar. • Strong hands-on experience building and operating cloud-native data platforms. • Strong programming experience using Java and/or Python. • Hands-on experience with real-time streaming and event-driven architectures, including Kafka, Kinesis or equivalent. • Experience with distributed data processing technologies such as Spark, Flink, Kafka Streams or equivalent. • Strong experience with AWS and/or Azure cloud environments. • Experience with cloud services such as S3, Glue, Lambda, RDS, Athena, EC2 or Azure equivalents. • Strong understanding of data platform architecture, data pipelines and distributed processing. • Experience with relational and NoSQL databases. • Strong SQL skills and understanding of data modelling and schema design. • Experience with CI/CD and DevOps practices. • Experience using Terraform or equivalent Infrastructure as Code technologies. • Experience with Docker and/or Kubernetes. • Experience using GitHub/GitLab and modern source control practices. • Experience implementing monitoring, logging and observability for platform services. • Experience supporting production systems and resolving technical and operational issues. • Understanding of platform security, resilience, scalability and availability. • Experience working within Agile and/or DevOps delivery environments. • Desirable: Helm, ArgoCD, Airflow, dbt, Bash, Ansible, Packer, Elasticsearch/OpenSearch, Prometheus, Grafana, ELK or Datadog. • Experience working within public sector, utilities or other regulated environments is advantageous. Data Platform Engineering As a Senior Data Platform Engineer, you will take ownership of complex platform engineering activities within your client delivery team. You will: • Build and maintain reliable data platform components and services. • Contribute to technical design and implementation decisions. • Develop reusable and maintainable platform patterns. • Support data ingestion, processing, storage and integration capabilities. • Identify platform risks relating to performance, scalability, security and reliability. • Contribute to platform performance tuning and optimisation. • Participate in code reviews and promote clean, maintainable engineering practices. • Support production troubleshooting and root cause analy