04/24/2026 updated
FW
100 % available
Senior Data Engineer | Palantir Foundry | PySpark | SQL | ETL/ELT
Poznań, Poland
Only remote
Bachelor of Engineering in Mechanical Engineering, Poznan University of TechnologyPython (Programming Language)
Palantir Foundry & Data Pipeline Development
Expertise in building and maintaining end-to-end data pipelines in Palantir Foundry, including ontology management (OMP), Workshop, Slate, Pipeline Builder, Code Repositories, Magritte, Quiver, and Contour. Hands-on experience with data source integration, ontology support, and migration of legacy pipelines into Foundry.
PySpark & Distributed Data Processing
Proficiency in processing and transforming large-scale datasets using Spark and PySpark in distributed environments, enabling efficient handling of big data workloads across client projects.
SQL & Data Modeling / ETL/ELT
Strong command of advanced SQL query development including joins, window functions, and CTEs for reporting and data extraction. Solid background in data modeling, ETL/ELT processes, and large dataset management across various business domains.
Python Scripting & Workflow Automation
Development of Python scripts for data automation, processing workflows, and automated data ingestion and preprocessing pipelines.
Cloud & DevOps: AWS, CI/CD, Data Governance
Familiarity with cloud infrastructure on AWS, CI/CD pipelines, and data governance practices to ensure reliable and compliant data operations.
Git, Docker & REST APIs
Experience with version control using Git, containerization with Docker, and integration of REST APIs in data engineering workflows.
Jira & Confluence
Usage of Jira and Confluence for project management, documentation, and collaboration in agile team environments.
Stakeholder Cooperation & KPI Definition
Collaboration with business stakeholders to define KPIs, reporting logic, and translate business requirements into data solutions.
Expertise in building and maintaining end-to-end data pipelines in Palantir Foundry, including ontology management (OMP), Workshop, Slate, Pipeline Builder, Code Repositories, Magritte, Quiver, and Contour. Hands-on experience with data source integration, ontology support, and migration of legacy pipelines into Foundry.
PySpark & Distributed Data Processing
Proficiency in processing and transforming large-scale datasets using Spark and PySpark in distributed environments, enabling efficient handling of big data workloads across client projects.
SQL & Data Modeling / ETL/ELT
Strong command of advanced SQL query development including joins, window functions, and CTEs for reporting and data extraction. Solid background in data modeling, ETL/ELT processes, and large dataset management across various business domains.
Python Scripting & Workflow Automation
Development of Python scripts for data automation, processing workflows, and automated data ingestion and preprocessing pipelines.
Cloud & DevOps: AWS, CI/CD, Data Governance
Familiarity with cloud infrastructure on AWS, CI/CD pipelines, and data governance practices to ensure reliable and compliant data operations.
Git, Docker & REST APIs
Experience with version control using Git, containerization with Docker, and integration of REST APIs in data engineering workflows.
Jira & Confluence
Usage of Jira and Confluence for project management, documentation, and collaboration in agile team environments.
Stakeholder Cooperation & KPI Definition
Collaboration with business stakeholders to define KPIs, reporting logic, and translate business requirements into data solutions.
Languages
GermanFluentEnglishFluentPolishNative speaker
Project history
Built and maintained data pipelines in Palantir Foundry, handling data source integration and ontology support. Processed and transformed large-scale datasets using Spark/PySpark in distributed environments. Wrote Python scripts for data automation and processing workflows. Developed advanced SQL queries for reporting and data extraction. Worked with data modeling, ETL processes, and large dataset management across client projects. Supported migration of legacy data pipelines into Palantir Foundry by refactoring transformation logic and aligning datasets with modern data modeling practices.
Developed SQL-based transformations for large retail datasets, wrote complex SQL queries (joins, window functions, CTEs) to extract and transform shopper behavior data across retail clients. Automated data ingestion and preprocessing workflows using Python. Modeled customer and store data into structured datasets. Collaborated with business stakeholders to define KPIs and reporting logic. Improved data quality through validation and consistency checks. Transitioned from reporting to building pipeline-based workflows. Designed transformation logic comparable to Foundry-style pipelines.