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.

Design and operate data processing layers for Zeta's AdTech platform, focusing on streaming and batch data pipelines. Collaborate with multiple teams to support ML features and analytics systems.

The Data Engineer will design and implement big data architectures and pipelines, optimize machine learning models, collaborate with stakeholders, and automate data processing using cloud services and CI/CD tools.

The Data Engineer will develop and maintain data pipelines, implement data transformation models, and enhance the data platform, collaborating with various 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.

The Data Engineer will design and implement data pipelines and architectures, support machine learning model deployment, and engage in data management and optimization strategies for big data environments.

Develop and maintain scalable data architecture and pipelines, ensuring data quality for analytics and business decision-making in collaboration with stakeholders.

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 will design and maintain data pipelines, optimize ETL processes, ensure data quality, and collaborate in an agile environment.

As a Data Engineer, you'll design and maintain ETL pipelines, write TypeScript code, and collaborate with stakeholders to ensure data quality and 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 Data Engineer will design and maintain scalable data pipelines, optimize data infrastructure, monitor data quality, and enable analytics capabilities, ensuring alignment with business goals.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

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.

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.

The Senior Data Engineer will design and build data pipelines, structure data, implement event tracking, and ensure data quality for a no-code platform.

As a Principal Database Engineer, you will architect scalable PostgreSQL solutions, ensuring data reliability, performance, and collaborating with teams to build a robust data platform for GitLab's growth.

We are seeking an AWS Developer to create a proactive security XDR solution, with experience in cloud solutions, Java, Python, and AWS services.

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.

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

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.

The Data Engineer will focus on infrastructure automation, reliability, and cost optimization. Responsibilities include designing Infrastructure-as-Code, managing CI/CD pipelines, establishing observability standards, and collaborating with teams to improve platform resilience.

As an Applied ML Engineer, you will build and scale data pipelines for video generation, ensuring data quality and optimizing preprocessing workflows.