Top Data Engineer Jobs in Prague

As a Data Engineer, you will develop data solutions for global banks, modernizing data processes and designing architectures while leading sub-projects.

Support the development of a standardized data platform, maintain data pipelines, assist with testing and troubleshooting data integrations, and learn data flows in financial and HR systems.

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

As a Data Engineer Manager, you'll lead a team in creating scalable data systems for trading strategies, ensuring high performance and reliability in data processing.

As a Data Engineer, you'll design, implement, and maintain data pipelines, collaborate with data teams, and optimize workflows to ensure data quality for trading initiatives.

Design, build, and optimize scalable Azure data pipelines and Lakehouse solutions using Azure Data Factory and Databricks. Integrate varied data sources, apply business logic, migrate legacy databases to cloud, and collaborate in Agile teams to deliver high-quality analytics-ready datasets.

As a Data Engineer, you will build Python applications for data processing, contribute to platform improvements, and support internal users. You'll work with data lakes and ETL tools in an agile environment.

The Data Engineer designs big data architecture, optimizes machine learning models, collaborates on data projects, and builds data pipelines.

The Data Engineer will design data pipelines and architecture, optimize machine learning models, and collaborate on data projects for international brands.

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 Data Engineer will design and maintain scalable data pipelines, optimize data infrastructure, monitor data quality, and enable analytics capabilities, ensuring alignment with business goals.

The role involves managing data collection for AI model training, operating cloud infrastructure, and collaborating with the AI team to enhance datasets.

The Staff/Lead Fullstack Engineer will enhance the Mimica Webapp by architecting scalable UI components, managing large datasets, and optimizing performance while collaborating with cross-functional teams.

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 Big Data Engineer will develop and maintain Big Data systems, optimize data pipelines, and collaborate on data-driven projects. Responsibilities include managing terabytes of data and working with various distributed storage and messaging systems.

Looking for a Software Engineer with 3-4 years of C++ experience to develop high-quality software, collaborate with teams, and participate in the full software development lifecycle.

As a Senior Data Engineer, you'll build and manage data pipelines, ensure data quality, and collaborate across teams, contributing to the Data Platform's growth.

Develop and maintain data pipelines, implement ETL processes, ensure data quality, and perform data modeling while mentoring junior engineers.

As a Senior Site Reliability Engineer, you will maintain a stable ecosystem for engineers in GCP, Kubernetes, and enhance observability while enforcing security measures. You'll automate processes, provide L3 support, and contribute to tool development.

As a Data Platform Engineer, you will design and implement scalable cloud-based data infrastructure, build CI/CD pipelines, and ensure platform reliability by implementing observability solutions, collaborating with teams to meet performance needs.

The Senior Data Platform Engineer will build scalable infrastructure for data independence, ensure data reliability, optimize cloud costs, and guide legacy migrations to a new data platform.

Develop and enhance ML models for search and recommendation; work with data engineers on ML components for production; research ML techniques.

As a Big Data Engineer, you will design and implement data processing systems, manage technologies like Hadoop and Spark, and build ETL processes to ensure data quality and performance.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

Design and implement AI projects, balance technical complexity with business impact, and collaborate with stakeholders to deliver value using AI and data.