Top Data Engineer Jobs in Italy

As a Data Engineer, build and manage data pipelines, ensure data quality, and support analytics for trading. Collaborate with teams to define data needs and best practices for infrastructure and applications.

The Data Engineer develops ETL/ELT pipelines, integrates data from various sources, and collaborates with teams to enhance data solutions and infrastructure.

As a Data Engineer at Zapier, you'll build scalable data systems, enhance product functionality through data, and collaborate with teams to improve data access and usability.

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.

As a Middle Data Engineer, migrate SQL Server data warehouses to Snowflake, refactor ETL processes, build data pipelines, and ensure reliable data movement.

This role involves optimizing database performance, managing data integrity, and establishing ETL processes. Responsibilities include database architecture, troubleshooting, and mentoring teams.

As a Data Engineer, you'll design, develop, and implement high-performance data infrastructure and pipelines while communicating effectively with various stakeholders.

Design and develop ETL data pipelines while improving data infrastructure and ensuring data quality using various technologies and tools.

As a Data Engineer at Camlin, you will design and implement data solutions, support data-related requirements, and enhance tools and applications by addressing issues. Collaboration with cross-functional teams and mentorship of peers is key.

The Data Engineer will design and implement scalable data solutions on AWS, manage data pipelines, enforce data governance, and collaborate with teams to enhance processes while troubleshooting challenges.

As a Backend Engineer, you'll develop Python microservices, upgrade analytics platforms, optimize data systems, and suggest UX improvements.

Design and architect scalable backend services, develop robust governance systems, build SaaS solutions, and mentor junior engineers to enhance IoT platform capabilities.

Develop data processing solutions using Google Dataproc, collaborate with teams, and support for data-related issues while writing technical documents.

Develop data processing solutions using Google BigQuery, support data-related issues, and collaborate with teams to deliver data-driven solutions.

Design Data Engineering solutions, lead development of machine learning models and applications, support presales activities by presenting and proposing solutions to clients.

Develop data processing solutions using Google BigQuery, collaborate with teams, and support data-related issues while ensuring clear communication.

Develop data processing solutions using Google Dataproc, support technical issues, and collaborate on data-driven solutions with teams.

The role involves developing data processing solutions with Google Dataproc, supporting data-related issues, and collaborating with teams to create data-driven solutions.

The role involves designing data engineering solutions, leading implementations including machine learning models, and supporting sales with technical proposals and client guidance.

Develop data processing solutions using Google BigQuery, collaborate with teams, and support data-related issues while ensuring high-quality documentation.

Design and implement data-oriented processes for managing multi-modal data, build data infrastructure on AWS, and develop data pipelines using various tools.

As a Data Engineer, you'll maintain and configure the Snowflake data platform, design integration pipelines, and innovate with new tools. Your role supports data security and performance while collaborating across teams.

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

As a Data Engineer at Nansen, you will build and optimize systems for their customer-facing analytics product, collaborating closely with crypto researchers and engineers to tackle large-scale data challenges and ensure data quality and reliability.

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