Data Platform Engineer - Snowflake
Deutsche Bank is hiring a Data Platform Engineer - Snowflake in Madrid, Spain. Level rates it ; you can apply on Deutsche Bank.
Level's read on this job
- Level rates this role Little AI ●○○○: aI is not part of the work.
- The posting mentions Snowflake, Terraform and data engineering among its tools and skills.
- Level classes it as a mid-level role.
- Deutsche Bank has 1,100+ other open roles on Level.
AI in this role
Data platform engineer focused on designing and building scalable cloud-based data platform components using Snowflake and Terraform.
Job Description:
Employer: DWS Group
Title: Data Platform Engineer - Snowflake
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 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
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
What we’ll offer you:
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. 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. We will continue to review and evolve our working environments and methods to ensure that we are working in the best way possible for our people.
If you require any adjustments or changes to be made to the interview process for any reason including, or related to a disability or long-term health condition, then please contact your recruiter and let them know what assistance you may need. Examples of adjustments include providing a change to the format of the interview, or providing assistance when at the DWS office. This will not affect your application and your recruitment team will discuss options with you.
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. The value we create for our clients and investors is based on our ability to bring together various perspectives from all over the world and from different backgrounds. It is our experience that teams perform better and deliver improved outcomes when they are able to incorporate a wide range of perspectives. We call this #ConnectingTheDots.
How we rate this
Data Platform Engineer - Snowflake at Deutsche Bank rates 0 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where cloud architecture was part of your work. What did you do?
- Tell me about a project where infrastructure as code was part of your work. What did you do?
- Tell me about a project where data pipelines was part of your work. What did you do?
- Walk me through how you've used Snowflake in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Data Engineering, Cloud Architecture, Infrastructure As Code, Data Pipelines, and Snowflake. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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