

Whitehall Resources
Cybersecurity Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Cybersecurity Data Engineer on a 12-month contract, hybrid in South Yorkshire. Pay rate is inside IR35. Key skills include Azure DevOps, ETL workflows, data pipelines, and programming in Python, PowerShell, and SQL.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
Unknown
-
🗓️ - Date
July 31, 2026
🕒 - Duration
More than 6 months
-
🏝️ - Location
Hybrid
-
📄 - Contract
Inside IR35
-
🔒 - Security
Unknown
-
📍 - Location detailed
South Yorkshire, England, United Kingdom
-
🧠 - Skills detailed
#Data Cleaning #Data Integration #Database Architecture #IAM (Identity and Access Management) #Azure Resource Manager #GitHub #S3 (Amazon Simple Storage Service) #Kafka (Apache Kafka) #Azure Databricks #Azure DevOps #Azure cloud #KQL (Kusto Query Language) #Azure #Azure Active Directory #Cybersecurity #Azure Event Hubs #Databases #Security #Java #DevOps #CLI (Command-Line Interface) #Data Lake #Datasets #Data Analysis #Containers #Kubernetes #Prometheus #Data Pipeline #Data Engineering #Synapse #Scripting #C# #Grafana #Data Manipulation #Deployment #Azure Log Analytics #Data Ingestion #Ansible #Azure Data Factory #Elasticsearch #ADF (Azure Data Factory) #Databricks #Big Data #Python #Spark (Apache Spark) #SQL (Structured Query Language) #Programming #Storage #Azure CLI (Azure Command Line Interface) #Automation #CHEF #Cloud #"ETL (Extract #Transform #Load)" #Linux #Terraform #Bash
Role description
Cybersecurity Data Engineer
Whitehall Resources are looking for a Cybersecurity Data Engineer. This role is hybrid working with 3 days per week onsite in South Yorkshire, and the remainder remote working, on an initial 12-month contract.
•
•
• Inside IR35
•
•
• Job Description:
• Ingestion and provisioning of raw datasets, enriched tables, and/or curated, re-usable data assets to enable Cybersecurity use cases.
• Driving improvements in the reliability and frequency of data ingestion including increasing real-time coverage.
• Support and enhancement of data ingestion infrastructure and pipelines.
• Designing and implementing data pipelines that will collect data from disparate sources across the enterprise, and from external sources, transport said data, and deliver it to our data platform.
• Extract Translate and Load (ETL) workflows, using both advanced data manipulation tools and programmatically manipulating data throughout our data flows, ensuring data is available at each stage in the data flow, and in the form needed for each system, service, and customer along said data flow.
• Identifying and onboarding data sources using existing schemas and, where required, conducting exploratory data analysis to investigate and determine new schemas.
Required Skills:
The successful candidate will be a student of the Google Site Reliability Engineering (SRE) philosophy as applied to managing large-scale cloud infrastructure, possess skills and experience within one or more of the following areas, and demonstrate a willingness to learn additional skills via certification and/or on-the-job learning where required.
Programming, Software & Network Principles:
• Experience with SRE and Azure DevOps
• Ability to script (Bash/PowerShell, Azure CLI), code (Python, C#, Java), query (SQL, Kusto query language) coupled with experience with software versioning control systems (e.g., GitHub) and CI/CD systems.
• Programming experience in the following languages: PowerShell, Terraform, Python Windows command prompt and object orientated programming languages.
• Demonstrable experience of Linux administration and scripting (preferably Red Hat Systems)
• Understanding of hardware and software principles and storage technologies (SSD, HDD, NVMe), CPU architectures, and Memory & Operating system principles (especially network stack fundamentals)
• Understanding of network protocols and network design
Data Engineering & Data Acquisition:
• Data Acquisition, Cloud-based Data Pipelines (Azure preferred)
• Data Transport and Data Cleaning
• Data Engineering pipeline automation, productionisation, and optimisation
• Designing, building, and maintaining data pipelines and ETL workflows across disparate datasets
• Cloud Cost optimisation
• Dataset and Data Asset Curation
• Data Modelling and Cataloguing
• Database Architecture and Design
• Data Warehousing and Data Integration
• Real-Time Analytics Deployment for Large-Scale Datasets
• Applying data engineering methods to the cyber security domain
Technology Stack:
• Technical knowledge and breadth of Azure technology services (Identity, Networking, Compute, Storage, Web, Containers, Databases)
• Cloud & Big Data Technologies such as Azure Cloud, Azure IAM, Azure Active Directory (Azure AD), Azure Data Factory, Azure Databricks, Unity Catalog, Azure Functions, Azure, Kubernetes, Service, Azure Logic App, Azure Monitor, Azure Log Analytics, Azure Compute, Azure Storage, Azure Data Lake Store, S3, Synapse Analytics and/or PowerBI
• Experience with server, operating system, and infrastructure technologies such as Nginx/Apache, CosmosDB, Linux, Bash, PowerShell, Prometheus, Grafana, Elasticsearch)
• Experience with Infrastructure-as-Code and Automation tools such as Terraform, Chef, Ansible, CloudFormation/Azure Resource Manager (ARM)
• Streaming platforms such as Azure Event Hubs or Kafka, and stream processing services such as Spark streaming
• Experience with Security Information & Event Management (SIEM) and Security Orchestration, Automation & Response (SOAR) technologies, especially cloud based, is a significant asset
Cybersecurity Data Engineer
Whitehall Resources are looking for a Cybersecurity Data Engineer. This role is hybrid working with 3 days per week onsite in South Yorkshire, and the remainder remote working, on an initial 12-month contract.
•
•
• Inside IR35
•
•
• Job Description:
• Ingestion and provisioning of raw datasets, enriched tables, and/or curated, re-usable data assets to enable Cybersecurity use cases.
• Driving improvements in the reliability and frequency of data ingestion including increasing real-time coverage.
• Support and enhancement of data ingestion infrastructure and pipelines.
• Designing and implementing data pipelines that will collect data from disparate sources across the enterprise, and from external sources, transport said data, and deliver it to our data platform.
• Extract Translate and Load (ETL) workflows, using both advanced data manipulation tools and programmatically manipulating data throughout our data flows, ensuring data is available at each stage in the data flow, and in the form needed for each system, service, and customer along said data flow.
• Identifying and onboarding data sources using existing schemas and, where required, conducting exploratory data analysis to investigate and determine new schemas.
Required Skills:
The successful candidate will be a student of the Google Site Reliability Engineering (SRE) philosophy as applied to managing large-scale cloud infrastructure, possess skills and experience within one or more of the following areas, and demonstrate a willingness to learn additional skills via certification and/or on-the-job learning where required.
Programming, Software & Network Principles:
• Experience with SRE and Azure DevOps
• Ability to script (Bash/PowerShell, Azure CLI), code (Python, C#, Java), query (SQL, Kusto query language) coupled with experience with software versioning control systems (e.g., GitHub) and CI/CD systems.
• Programming experience in the following languages: PowerShell, Terraform, Python Windows command prompt and object orientated programming languages.
• Demonstrable experience of Linux administration and scripting (preferably Red Hat Systems)
• Understanding of hardware and software principles and storage technologies (SSD, HDD, NVMe), CPU architectures, and Memory & Operating system principles (especially network stack fundamentals)
• Understanding of network protocols and network design
Data Engineering & Data Acquisition:
• Data Acquisition, Cloud-based Data Pipelines (Azure preferred)
• Data Transport and Data Cleaning
• Data Engineering pipeline automation, productionisation, and optimisation
• Designing, building, and maintaining data pipelines and ETL workflows across disparate datasets
• Cloud Cost optimisation
• Dataset and Data Asset Curation
• Data Modelling and Cataloguing
• Database Architecture and Design
• Data Warehousing and Data Integration
• Real-Time Analytics Deployment for Large-Scale Datasets
• Applying data engineering methods to the cyber security domain
Technology Stack:
• Technical knowledge and breadth of Azure technology services (Identity, Networking, Compute, Storage, Web, Containers, Databases)
• Cloud & Big Data Technologies such as Azure Cloud, Azure IAM, Azure Active Directory (Azure AD), Azure Data Factory, Azure Databricks, Unity Catalog, Azure Functions, Azure, Kubernetes, Service, Azure Logic App, Azure Monitor, Azure Log Analytics, Azure Compute, Azure Storage, Azure Data Lake Store, S3, Synapse Analytics and/or PowerBI
• Experience with server, operating system, and infrastructure technologies such as Nginx/Apache, CosmosDB, Linux, Bash, PowerShell, Prometheus, Grafana, Elasticsearch)
• Experience with Infrastructure-as-Code and Automation tools such as Terraform, Chef, Ansible, CloudFormation/Azure Resource Manager (ARM)
• Streaming platforms such as Azure Event Hubs or Kafka, and stream processing services such as Spark streaming
• Experience with Security Information & Event Management (SIEM) and Security Orchestration, Automation & Response (SOAR) technologies, especially cloud based, is a significant asset






