Senior Data Developer (m/f/d)

SmartRecruiters, Inc.; Kraków; On-site; PLN 180,000 - 240,000; Full time

Benefits offered by this job

B2B cooperation

Job summary

InPost, a leading European e‑commerce parcel delivery platform, seeks a Senior Data Developer in Kraków to join its Global Network Analytics team. You will transform data into a trusted foundation for decision-making, reporting and automation, combining engineering rigor with business insight.

You will design ETL/ELT pipelines, build data layers in Databricks, Data Lake and Delta Lake, automate data workflows, ensure data quality, and document processes in Confluence while using AI tools

Qualifications

• 2+ years in Data Engineering, Analytics Engineering or data analysis with ETL/ELT design experience
• Experience maintaining production data processes, monitoring and data quality
• 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
• Experience with Git and Azure DevOps across Dev/Test/Prod environments
• Ability to translate business requirements into technical solutions
• Advanced English for international collaboration
• Strong analytical thinking and prioritization under time pressure

Responsibilities

• Design, build and maintain ETL/ELT processes using SQL, PySpark and Python
• Develop data layers in Databricks, Data Lake and Delta Lake
• Automate and orchestrate data loading and transformation to reduce manual work
• Ensure data quality, consistency and reliability with validation rules and monitoring
• Optimize SQL queries, Spark processes and data storage for performance and cost
• Provide ready-to-use data to analysts, Product Owners and stakeholders
• Create and maintain technical documentation in Confluence
• Apply AI tools consciously with thorough verification before implementation

Skills

Analytical thinking

Business requirements translation

Attention to detail

Proactivity

Tools

SQL

Python

PySpark

Databricks

Azure

Git

Azure DevOps

Data Lake

Delta Lake

Job description

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 (Senior)Data Developeryou 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.
• 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