(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