Senior Data Developer
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Job Description
Senior Data Developer building ETL/ELT pipelines and Databricks data layers for InPost’s European parcel-delivery network. Ensuring reliable, governed data for analytics, reporting and automation.
Responsibilities:
- 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 for analytical, reporting and automation solutions
- Automate and orchestrate data loading and transformation processes
- Ensure data quality, consistency and reliability through validation rules, monitoring, alerting and incident diagnosis
- Optimize SQL queries, Spark processes and data storage structures for performance, stability, scalability and processing costs
- Provide reliable, ready-to-use data to analysts, Product Owners and other stakeholders
- Create and maintain technical documentation in Confluence covering data processes, models, KPI logic, dependencies, data lineage and incident-handling procedures
- Use AI tools as a work accelerator while verifying generated code, configurations and documentation before implementation
Requirements:
- At least 2 years of experience in Data Engineering, Analytics Engineering or data analysis
- Experience designing ETL/ELT processes and building data models or data layers for analytical purposes
- Experience 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
- Ability to translate business requirements into technical solutions
- Advanced English skills for confident communication in an international environment
- Analytical and logical thinking, attention to detail, proactivity and ability to prioritize work under time pressure
- Preferred: experience in a complex operational environment
- Preferred: knowledge of dimensional modelling, including star schema, fact and dimension tables, data grain, and normalization or denormalization approaches
- Preferred: knowledge of advanced Databricks and Delta Lake mechanisms
- Preferred: experience with Kafka, Structured Streaming or Event Hubs
- Preferred: familiarity with monitoring and alerting tools
- Preferred: knowledge of data security, access control, metadata management and data lineage principles
- Preferred: experience with Jira and Confluence
- Preferred: certifications such as Microsoft Certified: Fabric Analytics Engineer DP-600 or Databricks Data Engineer / Analyst Associate
Benefits:
- 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
- Visible immediate impact
- B2B type of cooperation
- Remote work available
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