Data Platform Engineer - Snowflake w Hiszpania, Polska

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. 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 a Data Platform Engineer, you will combine data and platform engineering expertise to design, build and continuously improve our cloud-based data platform.

Your responsibilities

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. * Work with your product owner to translate product vision and demand into actual implementations.

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. At DWS, you’ll have access to a range of benefits which you can choose from to create a personalised plan unique to your lifestyle. 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.

We are looking for: * 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. * Proficiency with IaC (e.g. 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. * Strong problem-solving skills, strategic thinking and attention to detail. * Fluent in English (written and spoken). * 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.