Senior Platform Engineer – Data & Analytics Platform

Joinimagine; Barcelona; Híbrido; EUR 90.000 - 130.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work model

Up to 25 days abroad

Bonus scheme

Pension

Employee shares program

Descripción de la vacante

Allianz Technology seeks an experienced Data Platform Engineer to design and deploy central platforms and data products. You will partner with OEs to deploy core components across Databricks, Azure Synapse, and Microsoft Fabric, building scalable data pipelines and governance into production.

You will extend platform capabilities to AI/GenAI use cases, ensure high availability and strong security, and drive end-to-end data governance and lifecycle practices across the organization.

Formación

• BS/MS in Computer Science, Information Systems, Engineering, or equivalent.
• 5+ years of hands-on experience implementing or engineering data and analytics platforms in enterprise environments.
• Significant experience with Databricks, including Delta Lake, Unity Catalogue, workflows, and production pipelines.
• Practical experience with Azure data services such as Azure Synapse Analytics and Microsoft Fabric.
• Strong data integration skills, covering ETL and ELT design, orchestration (e.g., Azure Data Factory, Airflow), and both batch and streaming sources.
• Solid engineering skills in Python and SQL, with experience building and maintaining production-grade code.
• Experience with CI/CD pipelines, source control management, and infrastructure-as-code (e.g., Terraform, Bicep).
• Working knowledge of platform security and governance concepts, including access controls, encryption, and data lineage.
• Familiarity with end-to-end Data Product Management, including governance, quality, and lifecycle management.
• Excellent communication and stakeholder management skills in English.

Responsabilidades

• Consult with OEs in the implementation and configuration of core platform components across Databricks, Azure Synapse, and Microsoft Fabric, from initial deployment through to stable production.
• Assist in building data integration pipelines that connect OE source systems to central platforms, using both batch and streaming patterns.
• Configure platform capabilities with high availability, strong access controls, and end-to-end observability.
• Extend the platform offering into AI and GenAI scenarios, including Azure AI Foundry, so that model-based use cases run on governed foundations.
• Partner directly with Operating Entities to translate business needs into working platform implementations and reusable solutions.
• Implement governance, security, and data control layers in line with financial services expectations for data handling, auditability, and operational resilience.
• Build and refine CI/CD and infrastructure-as-code pipelines to keep deployment cycles fast, secure, and repeatable.
• Collaborate closely with security, risk, compliance, architecture, and data governance teams to clear the path for platform adoption.
• Deliver reusable components, reference architectures, and engineering best practices that accelerate platform rollout across the group.
• Support the rollout of central platform solutions to the OEs, and build business-specific use cases on top of them.
• Coach and mentor engineers across the organisation, and drive continuous improvement in tooling, standards, and ways of working.

Conocimientos

Databricks

Azure Synapse

Microsoft Fabric

Python

SQL

CI/CD

Terraform

Bicep

Data governance

English communication

Educación

BS/MS in Computer Science or related field

Herramientas

Delta Lake

Unity Catalogue

Azure Data Factory

Airflow

Terraform / IaC

Kubernetes

Descripción del empleo

Allianz Technology seeks an experienced Data Platform Engineer to design and deploy central platforms and data products. You will partner with OEs to deploy core components across Databricks, Azure Synapse, and Microsoft Fabric, building scalable data pipelines and governance into production.

You will extend platform capabilities to AI/GenAI use cases, ensure high availability and strong security, and drive end-to-end data governance and lifecycle practices across the organization.