Top Data Engineer Jobs in Portugal

Build, operate, and scale governed data pipelines and curated lakehouse datasets on Azure to support analytics, operational intelligence, and AI-enabled use cases. Deliver production-ready PySpark/SQL transformations, manage pipeline monitoring and performance, document lineage and business rules, and collaborate with stakeholders to ensure secure, governed, and reusable data products.

The role involves building large-scale data systems for robotics AI training, focusing on data pipelines, storage, and workflows.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

Design and build scalable log ingestion pipelines, ensure system reliability, and optimize performance in a high-throughput environment.

This role involves designing and implementing large-scale big data platforms using Java and various big data frameworks, along with integrating systems and managing databases.

Lead strategy and operations for on-prem Kafka and support Perforce-based asset version control. Maintain mission-critical Linux services, automate with scripting and IaC, troubleshoot complex issues, coordinate with production/engineering/vendors, mentor teammates, and participate in on-call rotations.

The Big Data Engineer role requires strong hands-on experience with Big Data technologies, AWS services, and programming in Java or Scala.

Lead design and build scalable, secure data platforms and pipelines for AI/ML. Own ingestion, transformation, storage, quality, monitoring, and real-time/batch processing. Collaborate with data scientists and ML engineers, drive data modeling and MLOps best practices, ensure governance and mentor junior engineers.

Seeking Data Platform Engineers to design, build, and manage scalable data pipelines and analytic query engines while ensuring data integrity and performance optimization.

As a Data Platform Engineer/Platform Lead, you'll design, support, and optimize data platforms for digital products while collaborating with cross-functional teams and managing complex DevOps initiatives.

Own and architect the semantic layer and metrics/metadata for the data platform (Databricks/GCP). Build AI-ready models, enforce modeling and documentation standards, implement observability/testing for pipelines, enable self-serve analytics, and collaborate across product, clinical, and business teams to translate questions into reliable data solutions.

Develop and optimize end-to-end data pipelines for autonomous driving, ensure data quality, and support model training through efficient data management processes.

Design, build, and operate scalable data and AI platform capabilities. Create reusable abstractions, templates, and services for data pipelines and products. Integrate Generative AI for discovery and automation, ensure data quality, lineage, observability, security, and support cross-functional analytics and applied-AI teams.

Technical lead for Finance Technology data engineering: design and build scalable batch and real-time data pipelines (Hadoop/Spark/PySpark/Scala/Java), optimize data models and APIs, drive cloud-based data architecture (AWS/GCP/Azure), enforce governance/security, and mentor engineers to deliver enterprise financial data services.

Partner with Sales to design and demo AI-powered, data-driven solutions for life sciences clients using Komodo's Healthcare Map. Run live no-code analyses, build reusable demo assets, navigate AI governance and procurement, quantify ROI, mentor junior SEs, and feed product/AI roadmap input.

Lead design and delivery of scalable Data and AI solutions, mentor engineering teams, drive GenAI proof-of-concepts, align technical strategy with business goals, and influence cross-functional stakeholders.

Senior Data Engineer responsible for designing and implementing data solutions, ensuring data quality, and optimizing data systems.

The Data/AI Cloud Engineer will implement AWS data services, build ETL pipelines, optimize databases, and support data-driven solutions collaborating with technical teams.

Design, build, and operate scalable, secure data infrastructure including access control, financial reporting pipelines, cloud storage reliability, and data platform tooling. Collaborate with data scientists, analysts, and stakeholders to ensure data integrity, performance, cost-efficiency, compliance, and rapid recovery at petabyte scale.

As a Research Engineer, you conduct pioneering research in autonomous systems and develop models using large-scale data and advanced simulators, collaborating with scientists and contributing to high-quality publications.

Lead architecture and build control plane services for a petabyte-scale compute platform. Design multi-tenant resource management, intelligent scheduling, GPU and AI/ML workload orchestration, and Kubernetes operators. Drive integration with infrastructure teams, lead code reviews, set standards, and mentor engineers to deliver production-grade distributed systems.

The Technical Program Analyst will develop and automate applications using Microsoft Power Platform, focusing on ETL workflows and stakeholder collaboration for technical solutions.

Lead and grow the data engineering team to evolve a cloud-native data platform: design pipelines, improve ETL/ELT and orchestration, ensure data quality and governance, enable BI and data products, manage infrastructure budget, and enforce security and operational best practices while partnering with product and business teams.

Early-career Data & AI Engineer supporting client work and applied R&D. Prepare, clean, and validate heterogeneous data; build reproducible Python/SQL workflows; support ML and generative-AI tasks (embeddings, RAG, evaluation); prototype tools; document assumptions; participate in code review and translate project lessons into reusable assets.

Design and build scalable platforms for data ingestion and storage, collaborate with hardware engineers, and define engineering processes at Sift.