Top Data Engineer Jobs in Lisbon

As a Data Engineer, you will build and maintain data pipelines, ensure high data quality, optimize data systems and collaborate with teams to provide valuable insights from data.

The Software Engineer will manage data collection for AI model training, extending cloud infrastructure and collaborating with AI scientists to enhance data ingestion and processing.

As a Data Engineer, you'll design and maintain ETL pipelines, write TypeScript code, and collaborate with stakeholders to ensure data quality and performance.

As a Senior Data Engineer, design and maintain data pipelines, leverage AI for data optimization, collaborate with stakeholders, and ensure data quality.

Build and maintain data pipelines, features, and services for ML and analytics, work on APIs, microservices, and integrate LLMs while ensuring MLOps best practices.

Join the EDA team as a Senior Data Engineer to develop data products and optimize data warehouses. Collaborate on data modeling and analytics solutions.

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.

Landskill is seeking a Big Data Engineer with experience in big data tools and programming. Duties include data modeling, ETL, and integration, with a focus on personal and professional development.

Responsible for writing ETL processes, designing data warehouse architecture, preparing analytical reports, and technical elaboration of features based on data.

Lead the design and implementation of scalable cloud-based data pipelines and architectures, ensuring best practices, compliance, and data quality.

As a Data Engineer at Feedzai, you'll design and maintain data pipelines, validate data quality, collaborate with teams, and mentor junior engineers.

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

The Data Engineer will construct data pipelines, manage ETL processes, optimize SQL queries, and ensure data integrity, utilizing various tools such as Airflow, Python, and SQL.

The role involves developing and supporting data processing pipelines, collaborating with ML Engineers, and improving infrastructure while mentoring team members.

The Senior Data Engineer will develop and maintain data pipelines, support data analysis, ensure architecture meets business needs, and communicate with stakeholders.

Lead the design and development of scalable data pipelines and cloud data platforms. Collaborate with business and technical teams to deliver high-quality data solutions.

Design and implement scalable data pipelines using PySpark. Develop ETL processes, collaborate with teams, and prioritize product roadmaps for AI training datasets.

The role involves building and maintaining end-to-end data pipelines on AWS, ensuring data reliability, collaborating with teams, and staying updated with data engineering advancements.

The Senior Data Engineer will design, build, and maintain data pipelines and infrastructure, ensuring data reliability and performance while collaborating with cross-functional teams to deliver data-driven solutions.

As a Senior Backend Engineer, you'll develop backend services and APIs, collaborate with cross-functional teams, and ensure code quality and performance in a high-growth environment.

The role involves creating and automating infrastructure features for data platforms using Python, with a focus on distributed systems and collaboration within a global team.

The role involves automating OpenSearch operations by developing features in Python, collaborating with an international team, and providing expertise on data platforms.

As a Software Engineer on the data platform team, you'll automate data platform operations, write Python code, and collaborate on solutions within a distributed team.

Support migration of legacy SQL Server data to Snowflake on AWS, refactor ETL processes, optimize data movement and collaborate on QA and deployment.