Title: Data Platform Engineer - Snowflake
Join us at DWS, and you can be part of an industry-leading firm with a general 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 a Data Platform Engineer, you will combine data and platform engineering expertise to design, build and continuously improve our cloud-based data platform.
As Data Platform Engineer - Snowflake, you will:
Contribute to the end-to-end architecture and design of cloud data platform components, ensuring that solutions are scalable, secure and maintainable.
Collaborate with product owners and stakeholders to understand requirements, translate them into user stories and solution designs, and implement and test the resulting platform capabilities.
Design and develop reusable components for data ingestion, transformation and distribution that improve delivery speed, consistency and operational reliability.
Build and maintain infrastructure components using Terraform and other infrastructure-as-code and automation tools.
Collaborate with architects, security engineers, control functions, the Chief Data Office and other stakeholders to strengthen regulatory compliance, security and platform reliability.
At least three years of experience in platform engineering, data engineering or a related field, ideally with a strong focus on enterprise data platforms. A degree in Computer Science, Engineering, Information Technology or a related discipline is an advantage.




Strong expertise in the modern data stack with focus on Snowflake and solid data engineering fundamentals
Terraform), automation tooling, orchestration tooling (e.g. dbt, Airflow)
Very good programming skills in Python and/or Java
Experience with development utilizing software development life cycle (SDLC) tools including Git, JIRA, Artifactory and Github
Fluent in English (written and spoken)
Proven ability to leverage AI tools to enhance productivity, optimise workflows to solve business problems, while applying critical judgement 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 and 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.

📌 Data Ingenieur (m/w/d) (Madrid)
🏢 Deutsche Bank
📍 Madrid