Lead Engineer– Data Platform

Employer:              DWS Group Title:                       Lead Engineer – Data Platform Location:                Madrid Job Code:              placeholder for LinkedIn job wrapping About DWS: Today, markets face a whole new set of pressures – but also a whole lot of opportunity too. Opportunity to innovate differently. Opportunity to invest responsibly. And opportunity to make change. Join us at DWS, and you can be part of an industry-leading firm with a global presence. You can lead ambitious opportunities and shape the future of investing. You can support our clients, local communities, and the environment. We’re looking for creative thinkers and innovators to join us as the world continues to transform. As whole markets change, one thing remains clear; our people always work together to capture the opportunities of tomorrow. As investors on behalf of our clients, it is our role to find investment solutions. Ensuring the best possible foundation for our clients’ financial future. And in return, we’ll give you the support and platform to develop new skills, make an impact and work alongside some of the industry’s greatest thought leaders. This is your chance to achieve your goals and lead an extraordinary career. This is your chance to invest in your future. Read more about DWS and who we are here. Team / division overview 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.  Your responsibilities – 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  Lead architectural decisions, proofs of concept and adoption plans based on scalability, interoperability, security, operability and total cost of ownership  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  Partner with architecture, security, governance and application teams to ensure platform solutions meet enterprise standards and regulatory requirements  Remain hands-on in architecture and code, lead design and code reviews, mentor engineers and foster a culture of engineering excellence and continuous improvement  We are looking for  12+ years of experience in data or platform engineering, including designing and operating enterprise-scale data platforms; a relevant degree is advantageous  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