Lead Data Engineer (all genders)
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Job Summary
At Beiersdorf we want to help people feel good about their skin and our commitment goes far beyond caring for skin. For 140 years we have developed innovative skin and body care products for well-known brands such as NIVEA Eucerin La Prairie Hansaplast and Labello. We act according to our purpose WE CARE BEYOND SKIN and take responsibility for our consumers our employees the environment and society.
Behind every brand every product and every accomplishment are our more than 20000 employees. It is for them that we live an inclusive culture of respect and trust that is strongly aligned with our values CARE COURAGE SIMPLICITY and TRUST. We also embrace diversity by valuing the uniqueness of each individual and being committed to equal opportunities for all.
As a Lead Data Engineer you concept design implement and support data pipelines and databases within our Azure/Databricks Data & Analytics platform. You will always find the balance between individual requirements and stable solutions. You are open to new technologies and see them as an opportunity to enable even deeper insights into data. You will work closely with our project leads reporting consultants data scientist and cloud work together on global projects in mixed project teams. It is important to us that everyone can contribute their experiences and concerns to discussions.
Your main tasks are:
- Design and develop data pipelines within Azure and Databricks tech stack
- Code advanced data processing solutions within Azure and Databricks tech stack
- Concept and implement relational and NoSQL database solutions within Azure and Databricks
- Development/code management using Azure DevOps
- Manage our Data Lake House which stores structured semi-structured data and unstructured data
- Act as primary technical liaison to the Architecture Team ensuring alignment with standards and guidelines
- Establish and maintain a productive feedback loop between architectural design and implementation
- Mentor technically (no people management) mid-level Data Engineers in the team
- Bachelors or Masters degree in related field
- Several years of experience in Data Engineering or Software Development within cloud native environments.
- Deep operational expertise across the Azure ecosystem (Azure Data Factory Databricks Synapse ADLS Gen2 Azure SQL).
- Strong knowledge of Azure serverless and integration services (Functions Cosmos DB Event Hubs/Service Bus).
- Solid implementation of observability practices (logging metrics distributed tracing) and secure secrets management.
- Expert-level proficiency in Python with strong PySpark experience.
- Proficiency in at least one compiled/typed language (Scala Java or Go).
- Ability to write clean modular and performance optimized code.
- Demonstrated capability in technology scouting and evaluating emerging trends for practical business value.
- Multi-cloud exposure (AWS/GCP) and experience with streaming architectures (Kafka Spark Structured Streaming).
- Strong understanding of data governance concepts and CI/CD automation principles.
If you have any questions please check our application FAQ first. If your question is not answered there feel free to contact our Talent Acquisition Expert Melanie via.
Required Experience:
IC
About Company
We care for skin, we care for people and we care beyond skin. That is what makes us unique.
