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 (Senior)  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: • 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 . 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 immediately  • We offer B2B type of cooperation