(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 immediately
• We offer B2B type of cooperation