Experteer Overview In this role you will lead the data integration strategy for DWS Corporate Functions, shaping how data moves across cloud, on-premise, and SaaS platforms. You will partner with engineering, platform owners and business stakeholders to ensure secure, scalable data flows that support transformation initiatives. This position offers the chance to influence architecture standards and drive modernization away from legacy ETL towards cloud-native solutions. Your work will enable reliable, low-latency data feeds that underpin critical banking and asset management processes. Join a global team focused on responsible innovation and enterprise-wide data excellence.Compensaciones / Incentivos
- 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 (GCP-to-GCP, GCP-to-on-premise, application-to-application, batch/real-time/event-driven, API-led and CDC)
- Establish standards, patterns and best practices for data ingestion, transformation and distribution
- Modernise from legacy ETL to cloud-native integration services with risk-aware migration decisions
- Provide governance and design assurance across major initiatives and challenge designs where needed
- Design near real-time and real-time data processing solutions, including streaming pipelines and event-driven services
- Oversee reliable, scalable data feeds for market, reference, position, transaction, investment and operational data
- Offer hands-on technical leadership for strategic initiatives, including design reviews and PoCs
- Collaborate with engineering teams, platform owners and stakeholders to ensure secure, resilient, scalable, and operable solutions
- Mentor engineering teams and promote engineering excellence (DevOps, CI/CD, automation,



observability, documentation)
- Own technology risk, controls, architecture outcomes and operational stability for integration solutions
- Provide updates and technical guidance to senior management on strategy, progress, risks and decisionsResponsabilidades
- 10+ years in data integration, ETL, enterprise data engineering or integration architecture with senior technical leadership
- Strong practical knowledge of Google Cloud Platform services relevant to data engineering (GCS, BigQuery, Pub/Sub, Dataflow, Cloud Composer, Cloud Run, Kubernetes)
- Hands-on experience with StreamSets, Informatica PowerCenter/IICS, uFlow or comparable workflow orchestration
- Proven experience delivering streaming data pipelines using Kafka, Pub/Sub, Dataflow, Spark Streaming or similar
- Understanding of event-driven architecture, API-led integration, microservices data exchange and CDC patterns
- Experience designing enterprise integration frameworks, reusable components and data ingestion/transformation/distribution
- Experience with high-volume data feeds and low-latency processing in hybrid-cloud environments
- Ability to leverage AI tools to enhance productivity while maintaining responsible use of data and AI outputs
- Strong programming capability in at least one modern language, preferably Python
- Knowledge of data modeling, metadata management, data quality, data lineage and master data management
- Experience with Agile, DevOps, CI/CD and observability practices
- Experience in regulated financial services (Banking, Asset Management or Wealth Management) and understanding of asset management processes
- Bachelor's or Master's degree in Computer Science, Engineering or related field, or equivalent experienceRequisitos principales
- hybrid working model
- healthcare options
- retirement plan
- employee perks
- inclusive culture

📌 Data Integration Lead, Vice President (Madrid)
🏢 Deutsche Bank
📍 Madrid