Senior Data Developer (m/f/d)

Join our Global Network Analytics area
This is a role for someone who enjoys working close to data, understands both technical quality and business context, and wants to have a real impact on how data is prepared, validated and used by analytical, reporting and product teams.
As a Data Expert you will help transform data into a trusted foundation for decision-making, reporting and automation. You will combine technical engineering skills with business understanding, data quality awareness and a critical approach to AI-supported work
In this role, you will:
Design, build and maintain ETL/ELT processes using SQL, PySpark and Python, including integration of data from different source systems.
Develop data layers in Databricks, Data Lake and Delta Lake, including tables, views and data models used by analytical, reporting and automation solutions.
Automate and orchestrate data loading and transformation processes to reduce manual work, improve repeatability and lower the risk of errors.
Ensure data quality, consistency and reliability through validation rules, monitoring, alerting and incident diagnosis.
Optimize SQL queries, Spark processes and data storage structures with a focus on performance, stability, scalability and processing costs.
Provide reliable, ready-to-use data to analysts, Product Owners and other stakeholders as a foundation for analysis, reporting and automation
Create and maintain technical documentation in Confluence, covering data processes, models, KPI logic, dependencies, data lineage and incident-handling procedures
Use AI tools consciously as a work accelerator, while fully verifying generated code, configurations and documentation before implementation.
What we are looking for
At least 2 years of experience in Data Engineering, Analytics Engineering or data analysis, including experience in designing ETL/ELT processes and building data models or data layers for analytical purposes.
Experience in maintaining production data processes, including monitoring, issue diagnosis and data quality assurance.
Experience with cloud solutions, especially Microsoft Azure.
Practical knowledge of SQL, Python, PySpark and Databricks.
Understanding of Data Lake / Delta Lake architecture and data modelling principles.
Practical experience with Git and Azure DevOps, including managing changes across Dev, Test and Prod environments.
The ability to translate business requirements into technical solutions.
Advanced English skills, enabling confident communication in an international environment.
Analytical and logical thinking, attention to detail, proactivity and the ability to prioritize work under time pressure.
Nice to have
Experience working in a complex operational environment.
Knowledge of dimensional modelling, including star schema, fact and dimension tables, data grain, and normalization or denormalization approaches for reporting and analytics.
Knowledge of advanced Databricks and Delta Lake mechanisms.
Experience with streaming technologies such as Kafka, Structured Streaming or Event Hubs.
Familiarity with monitoring and alerting tools.
Knowledge of data security, access control, metadata management and data lineage principles.
Experience with Jira and Confluence.
Certifications such as Microsoft Certified: Fabric Analytics Engineer DP-600 or Databricks Data Engineer / Analyst Associate.

Employment type
Full-time

Work arrangement
Yes