Data Integration Lead, Vice President

About the role

DWS Corporate Functions Technology is looking for a Data Integration Lead, Vice President, based in Madrid. The role defines and delivers the data integration architecture for DWS Corporate Functions' global technology landscape, covering cloud, on-premise, SaaS and enterprise platforms in a regulated asset management environment. It provides technical leadership so that data moves securely, reliably and efficiently between platforms, services and applications.

Key responsibilities

• Define and evolve the enterprise data integration architecture and roadmap across cloud-native, hybrid, SaaS and on-premise ecosystems.
• Lead architectural decisions for integration scenarios such as GCP-to-GCP, GCP-to-on-premise, application-to-application, batch, real-time, event-driven, API-led and CDC-based integration.
• Set standards, frameworks and best practices for data ingestion, transformation, enrichment, distribution and integration.
• Drive modernisation from legacy ETL platforms toward cloud-native integration services.
• Provide technical governance and design assurance, and lead design of near real-time and real-time processing solutions, streaming pipelines and low-latency feeds for market, reference, position, transaction, investment and operational data.
• Partner with engineering teams, platform owners, architects and business stakeholders, mentor engineering teams and promote DevOps, CI/CD, automation and observability.
• Own technology risk, controls and operational stability, and report to senior management on strategy, progress, risks and key decisions.

Required profile

• 10+ years of experience in data integration, ETL, enterprise data engineering or integration architecture, with evidence of senior technical leadership.
• Experience in regulated financial services, preferably banking, asset management or wealth management; knowledge of asset management business processes is advantageous.
• Bachelor's or Master's degree in Computer Science, Engineering or a related discipline, or equivalent practical experience.

Required skills

• Google Cloud Platform services for data engineering and integration (GCS, BigQuery, Pub/Sub, Dataflow, Cloud Composer, Cloud Run, Cloud Functions, Kubernetes).
• Enterprise integration platforms such as StreamSets, Informatica PowerCenter / IICS, uFlow or comparable workflow orchestration tools.
• Streaming data pipelines with Kafka, Pub/Sub, Dataflow, Spark Streaming or comparable platforms.
• Event-driven architecture, API-led integration, microservices-based data exchange and CDC patterns.
• Data modelling, metadata management, data quality, data lineage and master data management.
• Agile, DevOps, CI/CD, cloud-native design and observability; strong engineering in at least one modern language, preferably Python.