Top Data Engineer Jobs in Portugal

The Lead Data Engineer will shape enterprise data solutions, lead a team in building data pipelines, ensure project execution meets standards, and mentor team members while focusing on scalability and performance improvements.

Lead design and implementation of scalable data architectures and pipelines (real-time and batch), mentor junior engineers, ensure pipeline reliability and security, adopt new tools, collaborate cross-functionally, and implement data governance.

As a Principal Data Processing Engineer, you will enhance a data processing engine, collaborate on open-source platforms, and optimize performance.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

As a Senior Data Engineer at GSTV, you will build and maintain data pipelines, ensuring data quality and collaborating with teams for scalable solutions and analytics support.

Design and develop scalable data processing systems and pipelines, create storage solutions, and ensure data integrity through testing and monitoring.

Design and develop scalable data pipelines and storage systems for machine learning evaluation, and create tools for data annotation and monitoring.

The Senior Software Engineer will develop and maintain big data applications, focusing on distributed computing, automation, and collaboration with teams to enhance healthcare solutions.

The Principal Software Engineer will provide technical and architectural leadership in data engineering, focusing on strategy, innovation, and ensuring successful production deliveries while fostering teamwork and mentoring.

Design, build, and maintain data pipelines, optimize performance and cost-efficiency, extend capabilities, and collaborate across teams to improve data governance and quality.

The role involves building and maintaining AI infrastructure, optimizing training performance, and developing tools for robot training and data workflows.

Maintain and enhance OT data systems to ensure data availability, integrity, security, and accessibility. Support monitoring, troubleshooting, and lifecycle management of high-availability OT architectures. Integrate control and data acquisition systems, enable analytics, lead projects, coach junior staff, onboard equipment, manage access, and drive IT/OT convergence and digitalization initiatives.

The role involves designing and implementing data pipelines and systems for large datasets, supporting scientific processes and experimentation.

Own end-to-end data science and ML work for B2C customers: build recommendation, forecasting, segmentation, and activation models; design A/B tests and causal analyses; create configurable multi-tenant model architectures; extract signal from sparse/noisy data; partner with engineering to productionize models and deliver analyses that change business decisions.

Lead and own the data science function: design and build production ML systems (recommendation, forecasting, segmentation), develop configurable multi-tenant models, run rigorous experimentation and causal analyses, connect model outputs to business impact, set scientific standards, and hire and mentor a high-velocity data science team.

Build and automate zero-config ingestion pipelines for major marketing and CRM platforms, transform third-party JSON into analytical schemas, map event data into unified identity/event streams, and integrate Martech data into the core ClickHouse/ML environment.

Design, implement, and deploy machine learning algorithms and scalable ML solutions; collaborate with data scientists, engineers, and federal customers to build analytics capabilities and features; support application deployment and customer enablement.

The role involves designing, building, and maintaining AWS infrastructure to support data science operations, optimizing cloud services, and collaborating with teams for scalable solutions.

Lead design and delivery of large data products and pipelines, mentor senior engineers, set standards and best practices, promote data/analytics across business units, collaborate on governance and curated data catalog, and present technical work externally.

The Software Data Engineer ensures secure data handling by supporting EDW operations, designing ETL processes, and automating data pipelines within a TS/SCI environment.

Lead design and delivery of Databricks-based Lakehouse solutions and end-to-end data engineering projects. Build and optimize ETL, streaming and batch pipelines, integrate cloud and on-prem systems, mentor team members, support pre-sales, and ensure governance, security, and platform performance.

Architect and scale cloud data platforms and ETL/ELT pipelines (batch and near-real-time), ensure data quality and observability, implement CI/CD for data infrastructure, collaborate with stakeholders and mentor junior engineers to deliver analytics and machine-learning-ready data products.

The Quality Assurance Engineer III oversees quality standards and audits, collaborates with development teams, and maintains automation frameworks, ensuring consistent testing across projects.

Ensure timely, high-quality data conversions from legacy systems to new platforms. Work with Implementation Specialists and Project Managers to execute conversion tasks, validate data integrity, troubleshoot issues, support deployments, and assist scheduling and customer communications.

The Software Data Operations Engineer analyzes systems, develops specifications, verifies implementation, and provides training while utilizing Microsoft technologies.