高级数据开发工程师 (m/f/d)
Senior Data Developer (m/f/d)
InPost 在波兰彻底改变了电子商务包裹配送，并已成为欧洲领先的户外（OOH）电子商务支持平台之一。由 Rafał Brzoska 于 1999 年创立，InPost 通过覆盖九个欧洲国家的超过 64,000 台自动包裹机（APM）和 30,000 多个自提和投递点（PUDO）网络提供配送服务：波兰、英国、法国、意大利、西班牙、葡萄牙、比利时、荷兰和卢森堡，同时还为电子商务商家提供门到门快递和履约服务。
InPost 的广泛 OO H 网络支持其市场中快速增长的包裹量，2025 年已交付 14 亿件包裹。其智能柜解决方案为消费者提供了更便宜、更灵活、更方便、环保且无接触的配送选择。作为领先的 OO H 物流提供商，InPost 因在欧洲重塑包裹配送经济而受到认可，通过其灵活、技术驱动的解决方案吸引消费者和商家。
加入我们的全球网络分析团队
这是一个适合喜欢贴近数据工作的人的职位，需要理解技术和业务背景，并希望对数据分析、报告和产品团队如何准备、验证和使用数据产生实际影响。
作为数据专家，你将帮助将数据转化为决策、报告和自动化的可信基础。你将结合技术工程技能与业务理解、数据质量意识以及对 AI 支持工作的批判性方法。
在这个职位上，你将：
· 使用 SQL、PySpark 和 Python 设计、构建和维护 ETL/ELT 流程，包括从不同源系统集成数据。
· 在 Databricks、Data Lake 和 Delta Lake 中开发数据层，包括分析、报告和自动化解决方案使用的表、视图和数据模型。
· 自动化和编排数据加载和转换流程，以减少手动工作，提高可重复性并降低错误风险。
· 通过验证规则、监控、警报和事件诊断确保数据质量、一致性和可靠性。
· 优化 SQL 查询、Spark 进程和数据存储结构，重点关注性能、稳定性、可扩展性和处理成本。
· 为分析师、产品负责人和其他利益相关者提供可靠、可用的数据，作为分析、报告和自动化的基础
· 在 Con 上创建和维护技术文档
查看英文原文
InPost has revolutionised e-commerce parcel delivery in Poland and is now one of Europe’s leading out-of-home (OOH) e-commerce enablement platforms. Founded in 1999 by Rafał Brzoska, InPost provides delivery services through a network of over 64,000 Automated Parcel Machines (APMs) and more than 30,000 pick-up and drop-off (PUDO) points across nine European countries: Poland, the United Kingdom, France, Italy, Spain, Portugal, Belgium, the Netherlands and Luxembourg, alongside to-door courier and fulfilment services for ecommerce merchants.
InPost’s extensive OOH network supports rapidly growing parcel volumes across its markets, with 1.4 billion parcels delivered in 2025. Its locker solutions offer consumers a delivery option that is cheaper, more flexible and convenient, environmentally friendly and contactless. As a leading OOH logistics provider, InPost is recognised for transforming parcel delivery economics in Europe, appealing to both consumers and merchants through its flexible, technology-driven solutions.
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 Expert 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