Top Data Engineer Jobs in Krakow

The Lead AI & Data Engineer will develop and enhance data engineering and analytics capabilities, focusing on scalable data ingestion, transformation, and integration with GenAI tools, while ensuring data quality and collaborating with cross-functional teams.

As a Backend Data Engineer, you will design and maintain data pipelines, implement features for marketing analytics, and collaborate with various teams while ensuring system performance and data quality.

The Data Engineer will design and maintain data models, develop BI solutions, integrate data, and optimize data flows while collaborating with stakeholders.

Develop scalable software, collaborate on design and architecture, conduct code reviews, and mentor new team members in a high-performance environment.

As a Data Engineer, you will develop and optimize data pipelines, implement advanced analytics, and collaborate with stakeholders to enhance data systems.

The Senior Software Engineer will lead engineering teams, mentor junior engineers, and ensure system reliability and performance while developing backend services.

The Principal Data Engineer will improve data pipeline architecture, optimize data flows, and support data projects for various teams in the company.

The Data Engineer will design and develop data pipelines and Lakehouse architectures using Azure Databricks, optimize data transformations, and integrate data from various sources, ensuring quality and performance.

The Data Engineer will design and implement scalable data platforms, build data pipelines, collaborate with teams to ensure data quality, and streamline processes using AWS services and big data technologies.

The Full Stack Data Engineer will design and build scalable data pipelines, optimize Snowflake architecture, develop dashboards and analytics solutions, and collaborate with cross-functional teams to ensure data reliability and meet business requirements.

We are seeking a GCP Data Engineer to build ETL/ELT pipelines, maintain dbt models, optimize BigQuery performance, and support data access in an international, remote team.

The role involves designing, developing, and maintaining backend systems, collaborating with cross-functional teams, and supporting continuous operations and availability of services.

The Data Engineer will develop, maintain, and optimize data pipelines using Apache Airflow, manage database performance, and support Elasticsearch integration. Responsibilities include building ETL scripts, handling Unix/Linux operations, and implementing CI/CD pipelines in GitLab.

Join Guesty as a Data Engineer to build and maintain scalable data systems, optimize ETL processes, and collaborate across teams for data-driven operations.

Develop reusable data pipelines, optimize ETL processes, build data integrations, and improve data platform architecture while collaborating with cross-functional teams.

The Big Data / Data Engineer will design and develop a big data processing engine and ETL pipelines, focusing on complex data analysis and architecture.

The Data Engineer will design and implement scalable data solutions, optimize ETL processes, and ensure data quality and compliance for a logistics network.

As a Data Engineer, you will design metrics, build reports, analyze data trends, and collaborate with cross-functional teams to enhance data-driven decision-making.

The Data Engineer will design and develop data pipelines using Azure Databricks, implement Lakehouse architectures, and integrate data into the platform, supporting BI teams and optimizing performance.

The Junior Data Engineer will analyze data, design experiments, build a marketing data stack, and collaborate with teams to improve data access and insights.

The Lead AWS Software Data Engineer will design and develop scalable data pipelines using Python and AWS tools, collaborate with business teams, and enhance data quality and observability while applying modern software engineering practices.

Design, build, and maintain scalable GCP data pipelines and ETL/reverse ETL processes using Dataflow, Dataform, and BigQuery. Develop secure APIs for ingestion, optimize data models and Datastream integrations, implement monitoring, and ensure GDPR/CCPA-compliant data governance for player analytics and fraud detection.

As a Data Engineer II, you will design scalable data pipelines in AWS, develop SQL transformations, and enhance MLOps workflows, focusing on analytics and machine learning initiatives.

The Data Engineer will design, build, and maintain scalable data pipelines, develop ETL workflows using Python and SQL, and optimize data processes to ensure reliability and performance.

The role involves designing, building, and maintaining scalable data systems, optimizing data models, writing SQL queries, and ensuring data quality in collaboration with data teams.