Data Engineer (Power BI, Python, Azure DevOps, PySpark)

Data Scientist

Expect more. Connect more. Be more at Diebold Nixdorf.  Our teams automate, digitize, and transform the way more than 75 million people around the globe bank and shop in this hyper-connected, consumer-centric world. Join us in connecting people to commerce in this vital, rewarding role.

Builds, deploys and supports the data and analytics infrastructure and tools required for scaling DN's expanding business. Designs, constructs and optimizes data management, database and related infrastructure and systems to meet varied and diverse business needs. Designs how data is stored, consumed, integrated and managed by different entities and digital systems. Collaborates with data consumers to determine, create and populate optimal data architectures, structures and systems. Plays a key role in selecting and configuring backend database technologies as required by business users.

Key Responsibilities

• Explore and analyze data to generate actionable insights.
• Collaborate with business stakeholders, data engineers, and analytics teams.
• Translate business needs into clear technical requirements.
• Ensure high‑quality analytical outputs.
• Structure, clean, and document datasets for reliable analysis.

 

Qualifications

Required

• 3 years of experience in data analysis or business analysis roles.
• Understanding of data and database concepts
• Strong proficiency in Python and SQL
• Experience in ETL/ELT processes or tools.
• Strong communication, attention to detail, and problem‑solving skills.

Preferred

• Experience in CI/CD and agile working concepts.
• Experience in Azure DevOps
• Experience in PySpark
• Exposure to Azure cloud data platforms
• Prompt engineering

 

Core Competencies

• Data Analytics – Strong understanding of analytical techniques as well as data structures and content.
• Analytical Thinking – Ability to break down problems and validate assumptions with data.
• Stakeholder Collaboration – Works well with diverse roles; asks the right questions.
• Documentation & Detail Orientation – Clear, structured writing; accuracy in specs.
• Adaptability – Comfortable working across multiple data domains and projects.

 

Sample Deliverables

• Business requirement collection and translation into technical requirements
• Data Analysis using descriptive statistics
• Data, Extraction, Transformation and loading as prerequisites for data analytic solutions
• Hypothesis testing
• Quality checks and test cases

 

Success Indicators

• High quality and clarity of analysis results
• Positive feedback from business and technical teams
• Independent and motivated personality

Required Qualifications

• Diploma or equivalent work experience required.
• Minimum of 2-4 years of relevant experience or equivalent combination of education and experience in Data Engineering.
• Good business English skills (Written and spoken).

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Why should you join Diebold Nixdorf?

Brightest minds + technology and innovation + business transformation  The people of Diebold Nixdorf are 23,000+ teammates of diverse talents and expertise in more than 130 countries, harnessing future technologies to deliver personalized, secure consumer experiences that connect people to commerce. Our culture is fueled by our values of collaboration, decisiveness, urgency, willingness to change, and accountability.

–Diebold Nixdorf is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity, age, marital status, veteran status, or disability status.

** To all recruitment agencies: Diebold Nixdorf does not accept agency resumes. Please do not forward resumes to our jobs alias, Diebold Nixdorf employees or any other organization location. Diebold Nixdorf is not responsible for any fees related to unsolicited resumes**

We are a global Company operating in multiple Locations and Entities. As we are keen to find the best solution for our candidates several legal entities might be applicable for a Job offer. A List of our operating entities can be found here - https://www.dieboldnixdorf.com/en-us/about-us/global-locations

Experience Level

Mid Level