Azure Data Engineer

Jobgether; Denmark; On-site; DKK 448,000 - 673,000; Full time

Benefits offered by this job

Remote work from anywhere

Exposure to Azure data services

Global team collaboration

Regulated financial services context

Professional growth opportunities

Job summary

Jobgether, on behalf of a partner company, seeks an Azure Data Engineer in Denmark to strengthen cybersecurity operations by engineering scalable data pipelines for SIEM and cloud platforms.

You will handle high volumes of security telemetry, ensure data quality, and collaborate with cloud, security, governance, and vendor teams to onboard sources and improve reliability while operating in a regulated financial services environment.

Qualifications

• 3+ years in cybersecurity or data engineering or related field.
• Experience onboarding, managing log sources in SIEM or cloud analytics.
• Strong data parsing, normalization, transformation and validation skills.
• Familiarity with cloud logging, monitoring, and analytics in Azure.
• Scripting/automation experience with Python or PowerShell preferred.
• Understanding of logging compliance, retention and data integrity.

Responsibilities

• Design, build, and maintain scalable security data ingestion pipelines for SIEM and Azure platforms.
• Parse, normalize, transform, enrich, and validate telemetry using regex and JSON parsing.
• Onboard new log sources and validate end-to-end data flows with multiple stakeholders.
• Ensure data quality, timeliness, and integrity for monitoring, detection, and reporting.
• Align data with schemas and governance standards to support analytics.
• Troubleshoot ingestion, parsing, and data-quality issues across environments.
• Maintain documentation on onboarding procedures, mappings, and configurations.
• Collaborate with security operations to support threat detection and investigation.

Skills

Azure Data Explorer

Log Analytics

Regex parsing

JSON parsing

Data transformation

SIEM pipelines

Python scripting

PowerShell

Security telemetry

On-prem/cloud

Tools

Azure Data Explorer

Log Analytics

Terraform

Python

PowerShell

SQL

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Azure Data Engineer based in Denmark.

This role offers the opportunity to strengthen cybersecurity operations by engineering reliable, scalable security data pipelines across cloud and on-premises environments.
You will work with high volumes of security telemetry and help ensure critical data is available for threat detection, incident response, compliance, and cyber risk visibility.
The position combines hands-on data engineering with cybersecurity, cloud technologies, automation, and data quality management.
You’ll collaborate with application, infrastructure, security, governance, and vendor teams to onboard and optimize diverse data sources.
The role is well suited to an engineer who enjoys troubleshooting complex ingestion challenges and improving system reliability and efficiency.
You’ll operate in a highly regulated financial services environment where data integrity, security, and operational excellence are essential.
This is an opportunity to make a direct impact on the organization’s ability to detect, investigate, and respond to cyber threats.

Accountabilities:

• Design, build, and maintain scalable security data ingestion pipelines for SIEM and cloud data platforms, including Azure Data Explorer and Log Analytics.
• Parse, normalize, transform, enrich, and validate structured and unstructured security telemetry using regex, JSON parsing, schema mapping, and other data-processing techniques.
• Partner with application owners, infrastructure and cloud teams, vendors, security stakeholders, and other internal groups to onboard new log sources and validate end-to-end data flows.
• Ensure the integrity, completeness, timeliness, and quality of security telemetry used for monitoring, detection, incident response, reporting, and risk management.
• Align security data with established schemas, naming conventions, governance standards, and organizational requirements to support downstream analytics and automation.
• Troubleshoot ingestion, parsing, transformation, schema, and data-quality issues across diverse platforms and environments.
• Maintain clear documentation covering log onboarding procedures, source requirements, data mappings, pipeline configurations, and operational support processes.
• Collaborate with detection engineering and security operations teams to ensure telemetry supports investigation, threat detection, response, and cyber risk use cases.
• Conduct telemetry gap analyses, identify missing or incomplete data sources, and recommend priorities for improving security coverage.
• Support logging practices that meet regulatory, audit, compliance, retention, and data-integrity requirements.
• Improve ingestion frameworks, automation, and onboarding processes to increase scalability, repeatability, reliability, and cost efficiency.
• Support infrastructure-as-code, scripting, and automation initiatives that streamline deployment and ongoing pipeline maintenance.
• Monitor pipeline performance and work with stakeholders to optimize ingestion reliability, throughput, and operational costs.
• Stay current with emerging cybersecurity telemetry formats, logging standards, data engineering practices, and cloud security data-platform capabilities.

Requirements:

• 3+ years of relevant experience in cybersecurity, data engineering, log management, security operations, or a related technology discipline.
• Hands-on experience onboarding, managing, and validating log sources within SIEM, cloud data platforms, or security analytics environments.
• Strong understanding of data parsing, normalization, transformation, and validation, including experience with regex, JSON, XML, CSV, and both structured and unstructured data.
• Familiarity with security telemetry from network, endpoint, identity, application, cloud, and infrastructure environments.
• Experience working with cloud platforms and associated logging, monitoring, and analytics services, particularly within the Azure ecosystem.
• Strong troubleshooting and analytical skills, with the ability to diagnose pipeline, ingestion, schema, and data-quality problems.
• Understanding of compliance and regulatory requirements related to logging, retention, auditability, and data integrity.
• Experience with scripting or automation technologies such as Python, PowerShell, or similar tools is preferred.
• Familiarity with query languages used to validate, investigate, and analyze ingested security data.
• Ability to coordinate complex onboarding initiatives across internal teams, vendors, and multiple stakeholders.
• Strong organizational skills and the ability to balance operational support, project delivery, and continuous improvement.
• Exceptional attention to detail and a strong sense of ownership for data quality and technical outcomes.
• Broader cybersecurity experience in areas such as threat detection, incident response, vulnerability management, or cloud security is an advantage.
• Strong communication, collaboration, judgment, and accountability, with the ability to work effectively within global teams.

Benefits:

• Remote work opportunity from anywhere.
• Opportunity to work on cybersecurity data engineering within a highly regulated financial services environment.
• Exposure to large-scale security telemetry, SIEM platforms, Azure data services, cloud environments, and security operations.
• Hands-on opportunities to develop scalable pipelines, automation, infrastructure-as-code, and data-quality solutions.
• Cross-functional collaboration with cybersecurity, cloud, infrastructure, application, governance, and vendor teams.
• Opportunity to contribute directly to threat detection, incident response, compliance, and cyber risk visibility.
• Professional growth through exposure to evolving cloud security, telemetry, and data engineering technologies.
• A collaborative global working environment with opportunities to solve complex technical challenges.