#WeAreIn for data that powers standout customer experiences. Do you want to build reliable, scalable data products that connect journeys across every channel? As a Data Engineer – Data Products on our Digital & Data team, you will design and operate platforms that make customer insights accurate, timely, and actionable. Are you in?
Your Role
Key responsibilities in your new role
In this role, you will build and run the data backbone behind Customer Journey Data Products, working closely with Data Product Owners, IT, and Data Quality specialists to deliver trustworthy analytics at scale.
-
Build and maintain pipelines: Build robust, well-tested ingestion and transformation pipelines; ensure they run reliably on a regular release cadence with clear ownership and monitoring
-
Build out the data quality framework: Help design and operationalize our DQ approach automated tests, validation checks, and Write-Audit-Publish gates on the gold layer plus the monitoring and alerting that catches issues before consumers do
-
Develop small data-collection web apps: Build lightweight internal web apps (e.g. forms, input tools, dashboards) that let business users submit data which feeds directly into our data products. You'll own this simple end-to-end frontend, backend, and the pipeline behind them
-
Data documentation and lineage: Maintain comprehensive docs for models, transformations, and business definitions to ensure data products are transparent, trustworthy, and ready for self-service consumption
-
Collaborate across functions: Work closely with data product owners, analysts, business stakeholders and IT/platform teams to translate business needs into well-modelled, trustworthy data
Your Profile
Qualifications and skills to help you succeed
To excel in this role, you combine strong modern data engineering fundamentals with a collaborative, product-oriented mindset to deliver high-quality customer data products on a scale.
-
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Electrical/Computer Engineering, or a related field
-
At least 2 years of hands-on experience in data engineering or analytics engineering
-
Solid SQL and Python/PySpark skills, with proven experience building and optimizing data pipelines and transformations on large datasets
-
Experience with orchestration tools like Apache Airflow, dbt, Mage AI, Prefect, etc
-
Proven experience building and maintaining ETL/ELT pipelines in production
-
Sound understanding of data modelling - especially dimensional modelling (fact and dimension tables); comfort building simple web apps - enough to ship an internal data-collection tool independently
-
Good communication and collaboration skills to work with Data Product Owners, IT, and Data Quality roles in a matrix organization
Please send us your CV in English.
Contact:
Mariana Pinho, LinkedIn
#WeAreIn for driving decarbonization and digitalization.
As a global leader in semiconductor solutions in power systems and IoT, Infineon enables game-changing solutions for green and efficient energy, clean and safe mobility, as well as smart and secure IoT. Together, we drive innovation and customer success, while caring for our people and empowering them to reach ambitious goals. Be a part of making life easier, safer and greener.
Are you in?
We are on a journey to create the best Infineon for everyone.
This means we embrace diversity and inclusion and welcome everyone for who they are. At Infineon, we offer a working environment characterized by trust, openness, respect and tolerance and are committed to give all applicants and employees equal opportunities. We base our recruiting decisions on the applicant´s experience and skills. Learn more about our various contact channels.
We look forward to receiving your resume, even if you do not entirely meet all the requirements of the job posting.
Please let your recruiter know if they need to pay special attention to something in order to enable your participation in the interview process.
Click here for more information about Diversity & Inclusion at Infineon.
