Secure Data Engineer

Who You Will Be Working With...

The Data Platforms team is part of the Insights and Data Global Practice and 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, Snowflake, Quantexa, Palantir, SAS.

As a Solution Architect with an Azure and Databrick focus, you will be an integral part of our team dedicated to building scalable and secure data platforms. You will leverage your expertise in Databricks, Apache Spark, and Azure to design, develop, and implement data warehouses, data lake houses, and AI/ML models that fuel our data-driven operations.

We are looking for a code first Data Engineer to design and build scalable and resilient data applications for Defence customers. This role sits at the intersection of Software Engineering and Data Engineering, working on mission critical systems where reliability, security and auditability are essential.

You will build data applications that process high volume and high velocity data, orchestrate complex workflows, and deploy your own solutions into secure containerised environments. You will work across the full lifecycle from development through to production, shaping architectures that support operational users, analytics, and AI enabled capabilities.

This role is hands on and engineering. You will write production grade code, contribute to secure platform patterns, and ensure that your data services run predictably in tightly governed Defence environments.

• Core Engineering
  Expert level Python and strong foundations in software engineering such as object oriented design, automated testing and version control.

• Data Engineering Stack
  Experience building pipelines using streaming frameworks, distributed processing engines and relational or analytical storage technologies.
  Examples include Kafka, Spark, Postgre
  
  SQL.

• Orchestration
  Experience defining and running data workflows using modern orchestration frameworks.
  Examples include Airflow, Dagster or Prefect.

• Data Quality and Lineage
  Familiarity with tools and techniques for data testing, documentation and lineage.
  Examples include Great Expectations or dbt.

• AI and MLOps
  Understanding of how to ope rationalise machine learning models in production, including model packaging, monitoring and controlled deployment.

• Containerisation and Kubernetes
  Confidence deploying applications in containerised environments, including defining services, pods and deployment configurations.

Examples include Docker and Kubernetes.

• Dev Ops Mindset
  Hands on experience with CI/CD approaches and a belief in owning the services you build.
  Examples include Git Lab CI, Git Hub Actions or Argo.

• Nice to have
  
  Experience with Infrastructure as Code or configuration management tools.
  Examples include Terraform or Ansible.
  Experience working in secure, restricted or air gapped environments, including Defence networks or MODCloud aligned platforms.
  Familiarity with Google Distributed Cloud (GDC) or other edge and on premises cloud platforms used in constrained or disconnected settings.

Your work will involve

Developing modular and maintainable software components that process, transform and expose data for analytical, operational or AI driven use cases. You will follow strong engineering practices, with testing and observability built in from the start.

Designing and implementing data ingestion and event driven patterns that support real time or near real time flows, ensuring they remain reliable even under demanding operational conditions.

Defining data workflows programmatically and managing complex dependencies, scheduling and error recovery behaviours within secure and assured environments.

Containerising your own services and deploying them into secure Kubernetes or cloud environments, using CI/CD principles adapted for Defence delivery. You will own your applications in production and contribute to secure patterns for deployment.

Implementing health monitoring, structured logging, metrics and lineage to meet Defence requirements for auditability, security and operational assurance. You will design systems that can self heal or fail gracefully when needed.

Provisioning the resources your services depend on using Infrastructure as Code and working closely with platform teams to ensure alignment with accredited Defence architectures.

Security Clearance:
To be successfully appointed to this role, must be eligible to obtain…