(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 Developer  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: What you will do • Build and maintain data solutions in Databricks using PySpark and SQL . You will work on new requirements as well as read, understand and extend existing notebooks and data processes. • Combine data from different systems and prepare reliable datasets for reports, operational processes and business users. • Create and maintain Delta tables, views and data models, including daily snapshots and reference or mapping datasets. • Translate business requirements into data logic in cooperation with analysts, Product Owners and international teams. • Investigate unexpected results, identify data issues and add practical checks for missing, duplicated or inconsistent data. • Maintain and improve scheduled Databricks jobs that support recurring business processes. • Keep code understandable and maintainable, and improve performance where it affects reliability or processing time. • Curiosity about new technologies and openness to exploring solutions beyond traditional data processing, including automation and containerized applications. • Document data processes, key business rules and common troubleshooting steps. 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 . Why join InPost? • Real ownership — your data products will directly influence strategic decisions • Opportunity to cooperate in a diverse, international, and cross-functional environment alongside leading experts • Space to experiment with new technologies — including AI tooling — and bring innovations into production • Your impact will be visible