Security Analytics Data Engineer | Azure & Power BI

Allianz Services Gmbh; Lisboa; Híbrido; EUR 60 000 - 90 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid work model

Up to 25 days abroad per year

Resumo da oferta

Allianz Group is a global leader in insurance and asset management. This role sits within the Digital Resilience as a Service framework, partnering with Group Information Security and Allianz Technology to transform security data into reliable risk insights and standardized reporting.

The environment combines cloud-based analytics, data pipelines, and advanced visualization to support enterprise decisions. You will build and govern data pipelines, dashboards, and AI-assisted analytics,

Qualificações

• Bachelor's degree in Computer Science, Data Science, Engineering, Information Security, or related field (or equivalent experience).
• Solid hands-on experience with Power BI (DAX, Power Query) for data modelling and visualization at a professional/advanced level.
• Experience with at least one cloud data platform (Azure Synapse, Azure Data Factory, or similar) and familiarity with data-lake or data-warehouse concepts.
• Working knowledge of a programming or scripting language for data manipulation (Python, PySpark, SQL, or similar).
• Experience working with data governance practices: data dictionaries, validation, documentation.
• Ability to communicate data insights clearly to non-technical stakeholders.

Responsabilidades

• Integrate data from SIEM, EDR, IAM, DLP, vulnerability management, ITSM, cloud, and HR systems to build a single source of truth for security metrics, leveraging Azure Cloud services (Synapse Analytics, Data Factory) and data-lake architectures.
• Design, build, and maintain automated data pipelines (PySpark, Azure Data Factory) for scheduled ingestion, transformation, and KPI/KRI computation (vulnerability remediation SLAs, patch cadence, phishing training outcomes, MTTR, control health, audit readiness, risk heatmaps, vendor risk, policy compliance).
• Build executive and operational Power BI dashboards with clear metric definitions, documentation, and governed datasets; implement scheduled refreshes, Row-Level Security (RLS), and dataset governance.
• Use Power BI (DAX, Power Query) and, where appropriate, Excel (Power Query, Power Pivot) for rapid prototyping, ad hoc modelling, and data validation.
• Work with cloud-based and on-premises data stores (Azure Synapse, SQL databases, MongoDB, or similar) to query, transform, and model security data at scale.
• Conduct ad hoc analysis, root-cause investigations, and trend reporting.
• Establish data dictionaries, lineage documentation, validation checks, and SOPs for data ingestion, transformation, and reporting.
• Maintain controls for data minimization, secure handling, encryption, and least-privilege access.
• Explore and apply Generative AI capabilities to enhance reporting and analytics workflows. For example, automating narrative summaries of dashboards, using NLP to surface patterns in unstructured security data, or building AI-assisted anomaly detection in risk metrics.
• Present findings and recommendations to stakeholders across SecOps, GRC, and IT, adapting the message to technical and non-technical audiences.

Conhecimentos

Power BI

Data modeling

Cloud data platform

Python/PySpark/SQL

Data governance

Communication

Formação académica

Bachelor's degree in Computer Science, Data Science, Engineering, Information Security, or related field

Ferramentas

Azure Synapse

Azure Data Factory

MongoDB

SQL databases/Excel (Power Pivot)

Descrição da oferta de emprego

Allianz Group is a global leader in insurance and asset management. This role sits within the Digital Resilience as a Service framework, partnering with Group Information Security and Allianz Technology to transform security data into reliable risk insights and standardized reporting.

The environment combines cloud-based analytics, data pipelines, and advanced visualization to support enterprise decisions. You will build and govern data pipelines, dashboards, and AI-assisted analytics,