Senior Data Engineer (Databricks)
⚲ Warszawa
22 000 - 27 000 PLN netto (B2B)
Wymagania
- Databricks
- Databases
- Relational Databases
- Azure
Opis stanowiska
About the Project
We’re looking for an experienced Senior Data Engineer to join a long-term data transformation project for an international company operating in the retail sector. You’ll work on a modern cloud-based data platform, helping to build scalable data solutions that support customer analytics, pricing optimization, inventory management, and business decision-making across multiple markets.
You’ll collaborate with data engineers, analytics teams, and business stakeholders to deliver reliable, high-quality data products using modern Data & AI technologies.
Your Responsibilities
• Design, build, and optimize scalable data pipelines using Databricks and Apache Spark.
• Develop and maintain ETL/ELT workflows for large-scale data processing.
• Build and manage data models based on Delta Lake architecture.
• Integrate data from multiple internal and external sources.
• Collaborate with Data Analysts, Data Scientists, and business stakeholders to deliver trusted datasets.
• Ensure data quality, performance, scalability, and reliability across the platform.
• Participate in architecture discussions and contribute to continuous improvements of the data ecosystem.
• Support CI/CD processes and infrastructure best practices.
Requirements
• 5+ years of commercial experience as a Data Engineer.
• Strong hands-on experience with Databricks.
• Excellent knowledge of Apache Spark and PySpark.
• Very good SQL skills.
• Experience working with Delta Lake.
• Hands-on experience with Azure cloud services (especially Azure Data Lake Storage and Azure Data Factory).
• Experience designing and maintaining modern ETL/ELT pipelines.
• Good understanding of data modeling principles and data warehousing concepts.
• Experience with Git and CI/CD practices.
• Strong communication skills and the ability to work in an Agile environment.
• Professional proficiency in English (B2+).
Nice to Have
• Experience with Apache Kafka or event-driven architectures.
• Knowledge of Terraform or Infrastructure as Code.
• Experience working with Power BI or other BI platforms.
• Familiarity with Azure DevOps.
• Experience supporting Data Science or Machine Learning initiatives.
What We Offer
• 100% remote work.
• B2B cooperation.
• Long-term international project.
• Rare visits to the client’s office when required.
• Opportunity to work with modern Data & AI technologies.
• Supportive and collaborative engineering environment.
• Flexible working hours.
• Competitive compensation.
About Remodevs
At Remodevs, we connect experienced IT professionals with carefully selected international technology projects. We partner with innovative companies across Europe, helping them build high-performing engineering teams while matching talented specialists with projects where they can grow, make an impact, and work with modern technologies.
We’re looking for an experienced Senior Data Engineer to join a long-term data transformation project for an international company operating in the retail sector. You’ll work on a modern cloud-based data platform, helping to build scalable data solutions that support customer analytics, pricing optimization, inventory management, and business decision-making across multiple markets.
You’ll collaborate with data engineers, analytics teams, and business stakeholders to deliver reliable, high-quality data products using modern Data & AI technologies.
Your Responsibilities
• Design, build, and optimize scalable data pipelines using Databricks and Apache Spark.
• Develop and maintain ETL/ELT workflows for large-scale data processing.
• Build and manage data models based on Delta Lake architecture.
• Integrate data from multiple internal and external sources.
• Collaborate with Data Analysts, Data Scientists, and business stakeholders to deliver trusted datasets.
• Ensure data quality, performance, scalability, and reliability across the platform.
• Participate in architecture discussions and contribute to continuous improvements of the data ecosystem.
• Support CI/CD processes and infrastructure best practices.
Requirements
• 5+ years of commercial experience as a Data Engineer.
• Strong hands-on experience with Databricks.
• Excellent knowledge of Apache Spark and PySpark.
• Very good SQL skills.
• Experience working with Delta Lake.
• Hands-on experience with Azure cloud services (especially Azure Data Lake Storage and Azure Data Factory).
• Experience designing and maintaining modern ETL/ELT pipelines.
• Good understanding of data modeling principles and data warehousing concepts.
• Experience with Git and CI/CD practices.
• Strong communication skills and the ability to work in an Agile environment.
• Professional proficiency in English (B2+).
Nice to Have
• Experience with Apache Kafka or event-driven architectures.
• Knowledge of Terraform or Infrastructure as Code.
• Experience working with Power BI or other BI platforms.
• Familiarity with Azure DevOps.
• Experience supporting Data Science or Machine Learning initiatives.
What We Offer
• 100% remote work.
• B2B cooperation.
• Long-term international project.
• Rare visits to the client’s office when required.
• Opportunity to work with modern Data & AI technologies.
• Supportive and collaborative engineering environment.
• Flexible working hours.
• Competitive compensation.
About Remodevs
At Remodevs, we connect experienced IT professionals with carefully selected international technology projects. We partner with innovative companies across Europe, helping them build high-performing engineering teams while matching talented specialists with projects where they can grow, make an impact, and work with modern technologies.
🔍 Dekoder Ogłoszenia
🔴
long-term data transformation project
Projekt może być długoterminowy, ale jego zakres i cel mogą ewoluować, co może prowadzić do zmian w wymaganiach lub technologiach.
🔴
modern cloud-based data platform
Chociaż brzmi nowocześnie, może oznaczać, że platforma jest w fazie rozwoju lub wymaga znaczących usprawnień, a nie jest w pełni dojrzała.
🟡
collaborate with data engineers, analytics teams, and business stakeholders
Oznacza to konieczność częstej komunikacji i negocjacji z różnymi grupami, co może być czasochłonne i wymagać umiejętności zarządzania oczekiwaniami.
🔴
deliver reliable, high-quality data products
Definicja 'niezawodnych' i 'wysokiej jakości' może się różnić w zależności od perspektywy biznesowej, co może prowadzić do nieporozumień co do priorytetów.
🟡
Participate in architecture discussions and contribute to continuous improvements of the data ecosystem
Może oznaczać zarówno realny wpływ na architekturę, jak i jedynie udział w dyskusjach bez faktycznej możliwości wprowadzania zmian.