Title: Lead Engineer – Data Platform
Join us at DWS, and you can be part of an industry-leading firm with a integral presence. You can support our clients, local communities, and the environment.
As investors on behalf of our clients, it is our role to find investment solutions. DWS’s data infrastructure team provides the secure, scalable and trustworthy foundation for storing, processing and distributing critical enterprise data. As Lead Engineer - Data Platform, you drive the design, built, and continuous improvement of our hybrid data platform. You’ll lead a small but high-impact team, setting technical direction, mentoring team members and contributing directly to architecture and code.
As our Lead Engineer – Data Platform, you will:
Own the end-to-end architecture, design and evolution of enterprise data platform capabilities across hybrid cloud and on-premises environments
Define the technical roadmap, engineering standards and reusable patterns for workflow orchestration, scheduling, dependency management and data processing
Establish reliability, observability and operational standards for data platform components, including monitoring, alerting, failure recovery, capacity management and service-level objectives
Drive platform automation through infrastructure as code, CI/CD, automated testing and self-service engineering capabilities
12+ years of experience in data or platform engineering, including designing and operating enterprise-scale data platforms; Deep hands-on Snowflake expertise across architecture, ingestion, transformation, workload management, performance, cost optimisation, secure data sharing and governance
~ Strong production experience with Apache Airflow, including reusable DAG patterns, dependency management, scheduling, testing, monitoring and failure recovery
~ Strong expertise in Apache Kafka and event-driven architectures, including topic design, producers and consumers, schema management,



Kafka Connect, delivery semantics and replay strategies
~ Proven ability to integrate batch and streaming pipelines across Snowflake, Airflow and Kafka
~ Advanced Python and SQL skills; Java experience for Kafka-based services and connectors is beneficial
~ Strong experience with Terraform, Git, CI/CD and automated testing; OpenShift or Kubernetes experience is desirable
~ Strong understanding of reliability, observability, data quality, security, access management and compliance in regulated environments
~ Strong problem-solving and strategic-thinking skills, with fluent written and spoken English
~ Proven ability to leverage AI tools to enhance productivity, optimise workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs

At DWS we’re serious about diversity, equity and creating an inclusive culture where colleagues can be themselves sand it’s important to us that you enjoy coming to work - feeling healthy, happy and rewarded. Whether you’re interested in healthcare, company perks, or are thinking about your retirement plan, there’s something for everyone.
DWS’ Hybrid Working model is designed to find the right balance between in-person collaboration and engagement in the office, which is core to our working culture, and working from home. Each business group varies on the split between time spent in the office and at home, but this will be discussed and made clear as part of your application and interview process. Examples of adjustments include providing a change to the format of the interview, or providing assistance when at the DWS office. We at DWS are committed to creating a diverse and inclusive workplace, one that embraces dialogue and diverse views, and treats everyone fairly to drive a high-performance culture. It is our experience that teams perform better and deliver improved outcomes when they are able to incorporate a wide range of perspectives.

📌 Lead Engineer- Data Platform (Madrid)
🏢 Deutsche Bank
📍 Madrid