Data Engineer

About Us

At Mercedes-Benz, we don't just build cars, we create great software.

We develop tomorrow's mobility together in our product lines, pushing the digitization of the Mercedes-Benz Group AG forward. As a tech company, we are agile, innovative and always keep our finger on the pulse of change. This is why inner source, FOSS, secure code, DevOps, infrastructure as code (IaC), data analytics, artificial intelligence and many more are core components of our daily work.

IT is our passion, and we move towards a bright future, sometimes quickly, sometimes creatively but always together.

We believe in integrity, trust and transparency as part of our flexible work culture and a strong emphasis on team work and the learning process, making mistakes and achieving continuous progress together in all products we create and develop within the Mercedes-Benz Group.

Our workplace is anywhere* with a fast connection either remotely at home, at your favorite caf or at our integrated office at Wisma Mercedes-Benz that comes with an LRT station at its doorstep, our al fresco cafeteria, ample greenspaces and free parking.

Job Objectives

Requirements analysis and customer consulting for analytics topics.

Identification, extraction, transformation and loading of data.

Storing data in relational, multidimensional, and NoSQL databases or data lakes both on-premises and in the cloud.

Modelling of data according to common methods for further processing.

Testing and quality assurance of data.

Use of source control and CI/CD processes.

Analyse linking of data using SQL, statistics, and data science to generate new insights.

Visualize data taking into account best practices such as information design with popular reporting and dashboarding systems.

Provide data through file sharing or REST APIs.

Creation of data architectures based on public cloud services.

Collaboration in agile projects.

Experience (type of)

Experience with Agile methodologies

Experience with Enterprise technologies

Experience with Product Oriented Teams

Programming or Data Architecture related certification

Specific knowledge/ Skill

Excellent communication skills

Good customer service orientation

Analytical, passionate and drives technology and product quality

Result-oriented thinking and action

Level 3:

Knowledge and Skills:

Knows the basics of data modeling, e.g. Kimball, Immon, DataVault, DataMesh.

Knows the basics of data transformation using SQL, popular programming languages and ETL tools.

Knows the basics of SCRUM.

Responsibility and Scope for decision-making:

Defines, documents and independently develops ETL routes, reports and dashboards.

Uses CI/CD processes.

Level 4:

Knowledge and Skills:

Has in-depth experience in data modeling.

Optimizes the performance of database queries

Automates CI/CD pipelines.

Advises clients on the use of analytics for data-driven decisions.

Models analytics architectures.

Leads projects according to agile methods.

Shares the best practices.

Independently educates oneself further.

Responsibility and Scope for decision-making:

Advises clients on the selection of target architectures, methods and tools.

Defines appropriate data modeling methodologies.

Participates in the definition of project standards and conventions.

Supports customer acquisition.

Integrates new employees into the team and project.

Manages small to medium-sized projects.

Level 5:

Knowledge and Skills:

Has expertise in data modeling, data architectures for complex analytics architectures and requirements analysis.

Independently educates oneself further and derives necessary changes for the team and the project.

Has expert knowledge in the implementation and definition of reports and dashboards.

Responsibility and Scope for decision-making:

Independently advises clients on analytics systems and supports the development of data-driven decisions.

Independently acquires new projects and products.

Builds project and product teams.

Supports the further development of team members.

Delegates development tasks.

Controls large or complex analytics projects.

Connects and shares his/her knowledge within the company.

Technical:

SQL/noSQL, Python or R, Microsoft Power BI, Cloud Computing and Data Architectures