Senior Azure Data Engineer

• Salary: Gross monthly salary between EUR 5,876 and EUR 8,395 (scale 10).
• Extras: a thirteenth month, 8% holiday allowance, and a 10% Employee Benefit Budget.
• Development budget: EUR 1,400 development budget per year for your growth and development.
• Hybrid working: a balance between home and office work (possible for most roles).
• Pension: decide for yourself the amount of your personal contribution.

Or view all our benefits.

Senior Azure Data Engineer – Information Factory Payments / Cluster Data Tribe Payments & Savings

Join Rabobank as a Senior Azure Data Engineer at the Information Factory Payments & Savings (IFP) and help drive strategic goals with data-driven decisions. IFP is a key data warehouse that processes vast amounts of payments and savings data daily, transforming it into valuable information products. We support business partners with insights and overviews of their products and processes, and handle external reporting to regulators and other organizations.

You and your job

• Developing and implementing new functionalities in the Information Factory Payments & Savings
• Creating new ETL processes from scratch to fetch data, integrate it into our data warehouse and prepare it (dimensional data modelling) to be used in front-end reporting
• Collaborate with cross-functional teams to ensure seamless integration of data solutions and standards

Practical examples

• Dashboards for product managers to assist them in product development and tapping into new markets
• Report functionality and operational datasets used in our daily banking to serve our customers
• Regulatory reporting to the Dutch National Bank and the Dutch tax authority

As an Azure Data Engineer, you are working on the back-end side. You bridge the gap between raw data and meaningful insights and ensure our organization can efficiently use this information.

Facts & Figures

• 36 hours per week
• Join our team and work with over 350 database tables containing more than 40 terabytes of data
• 43,822 Rabobank colleagues around the world

Top 3 responsibilities

• Be a senior guide for junior colleagues, presenting complex solutions clearly and taking initiative to improve development standards, workflows, technical configurations, and team alignment
• Develop and Implement: Create and implement new functionalities, working with developers, testers, and business analysts to refine and execute the best solutions
• Data Management & Modelling: Develop new ETL processes, integrate data into the data warehouse, and prepare it for front-end reporting

You will lead team development activities, including data governance, security, monitoring, maintenance, and troubleshooting in case of high-priority issues in production. You optimize performance to improve loading times. Supporting our solution architect to design future-proof, effective, and efficient solutions for new requirements. Finally, you will stay updated with the latest industry trends and technologies to enhance data engineering practices.

You and your talent

• HBO or University degree, preferably related to IT, computer science and/or data engineering
• Minimum of 5 years of experience as a Data Engineer / DWH Developer in a complex IT landscape
• Expert in ETL development, including proven experience with Databricks and Azure Data Factory
• Expert in RDBMS, SSMS, and writing and optimizing SQL queries
• Knowledge and experience in GIT and data modelling, preferably dimensional modelling (for example Kimball)
• Knowledge and experience with configuring and managing Azure resources
• Highly pro-active and motivated personality, you show initiative and take ownership
• Excellent analytical and problem-solving skills
• Experience with DBT, Python, Powershell and PowerBI is a big plus

This position is in Utrecht, in salary scale 9 or 10, depending on your knowledge and experience.

If you do not meet all the requirements but firmly believe that you can make a valuable contribution, do not hesitate to send us your motivation

Together we achieve

We believe in the power of difference. Bringing together people's differences is what makes us an even better bank. So we are very curious about what you can bring to our team at IFP.

‘As a team we combine business insights and technical skills to co-create solutions that turn data into direction. Asking questions, challenging ideas, and learning from each other is how we move forward. Together, we bring clarity to complexity!’ Dirk van Hoeij, Senior Azure Data engineer

Working together is the way we work; as 1 data-minded team at Rabobank. Speaking of Rabobank: we are a Dutch bank that operates in 38 countries for over 9,500,000 customers. Together with these customers, our members and partners we stand side by side to create a world in which everyone has access to enough healthy food. In the Netherlands, we work to create a country in which people are happy with how they live, work and do business.

You and the job application process

• Please upload both your CV and motivational letter with answers to our 2 questions. Applications missing either document cannot be considered
• Any questions about the job content? Contact Jeroen Wolfs, Tech Lead Cluster Payments & Savings Data, via jeroen.wolfs@rabobank.nl
• Any questions about working at Rabobank and the process? Contact Niels Diks, Recruiter IT via Niels.Diks@rabobank.nl
• If you are invited for an interview, Bo, our virtual assistant, will contact you via SMS and email to schedule it
• To be considered for this position, you must be located in the Netherlands or elsewhere in the EU and have the legal right to work in the Netherlands. We are unable to consider candidates requiring relocation from another country.
• Answers to frequently asked questions can be found at rabobank.jobs/nl/veelgestelde-vragen
• A reliability check is part of the procedure.
• We respect your privacy.
• #LI-ND1

Instead of a standard motivational letter, we are asking you to provide us with the answers to the following 2 questions (max 200 words per answer):

• What interests you specifically about this role?
• Can you give an example of a complex problem you encountered in a data ware house environment, why it was complex and how you solved that problem?