Top Data Engineer Jobs in Portugal

The Data Architect will design scalable data models, transform raw data into actionable insights, and deploy analytics solutions for healthcare providers, with a strong emphasis on SQL proficiency and cloud technologies.

Lead design, integration, testing, and deployment of tactical data link and communications capabilities (Link 22/Link 16). Develop software requirements, MBSE artifacts, and interoperability/interface definitions. Support developmental and operational test/evaluation, acquisition documentation, and advise program leadership on performance, schedule, and cost. Interface with DoD, USAF, Army, and joint stakeholders.

Partner with portfolio-company leaders to translate business problems into quantitative frameworks, build predictive models and analyses, and drive strategy and execution. Lead AI assessments, identify growth opportunities, present recommendations to executives, and implement measurable data-driven initiatives across finance, pricing, operations, and marketing.

The Senior Data Engineer will design and operate the data platform, build ELT/ETL pipelines, optimize data performance, and ensure data quality while collaborating with business teams.

Lead enhancement, integration, and support for IBM InfoSphere MDM and Kafka-based integrations. Develop specs, troubleshoot production, manage deployments (WildFly), automate scripts, run SQL, support CI/CD, collaborate with DBAs and infra teams, and deliver testing, UAT, and monthly application reporting.

The Cloud Data Services Engineer will support Cloud Data Services, perform database design, and implement DevOps practices in a high-performance team environment.

The Cloud Data Services Engineer will support Cloud Data Services, focusing on SQL Server and NoSQL technologies. Responsibilities include database design, performance monitoring, and automation within a DevOps environment.

The Cloud Big Data Engineer role focuses on supporting Cloud Data Services, involving database design, performance monitoring, and troubleshooting in a fast-paced environment. The role requires expertise in Microsoft SQL Server, NoSQL, and cloud application administration, while embracing DevOps practices for continuous integration and automated quality checks.

The Cloud Data Services Engineer will design and implement solutions, support production databases, plan procedures, and evaluate new cloud technologies.

The role focuses on building a Data Management Cloud Platform using Java and AWS technologies. Candidates are expected to have extensive experience in Big Data, automation, and CI/CD pipelines, along with knowledge of streaming architecture and tools like Kafka and Spark.

Develop and maintain infrastructure for market data feeds, focusing on performance and latency in a real-time financial environment.

As a Staff Data Engineer on the Data Lake team, you will architect, build, and scale distributed ETL pipelines, ensuring data quality and leading the engineering team. You will also drive large-scale data processing and technical initiative leadership.

Develop and maintain thermofluid, lumped-parameter models and simulation tools for the Raptor engine; perform engine cycle analysis and anomaly resolution; build data pipelines, automation, and web tools to translate test data into flight predictions; collaborate across teams to improve interoperability, vehicle-integrated models, and software used for GNC and flight performance prediction.

The Sr. Data Engineer will develop KPIs for infrastructure costs, analyze data, create reports, and enhance data systems for Starlink's ground network.

Develop, maintain, and improve lumped-parameter thermofluid models and simulation tools for the Raptor engine; perform engine cycle analysis, anomaly resolution, data-driven root cause analysis, and generate automated predictions for test and flight performance. Build tooling, data pipelines, and integrations to support GNC, flight software validation, and cross-team interoperability.

As a Staff Software Engineer on the Storage Platform team, you will design distributed storage systems, improve database reliability and performance, build automation for database management, and ensure high availability for user-facing products.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

As a Training Manager/Curriculum Developer, design and deliver training programs in Intelligence, Cyber, Data Science, and AI, collaborating with SMEs to create impactful curriculum.

Design and develop ETL processes and data structures for banking data warehousing. Mentor junior developers and ensure solution alignment with business strategies.

The Senior Data Engineer will design and maintain data pipelines and infrastructure for fraud detection analytics, ensuring data integrity and supporting testing across platforms.

The role involves building data processing pipelines, deploying cloud technologies, and writing code in a Kubernetes environment, focusing on big data technologies.

Senior Software Engineers will build data processing pipelines and deploy cloud technologies, focusing on big data and machine learning infrastructure. They are expected to write and deploy efficient code within a Kubernetes environment.

Build and operate reliable infrastructure and systems that support research workflows. Improve cluster bootstrapping, provisioning, automation, and deployment. Debug networking, compute, storage, orchestration, and reliability issues. Write software and automation to reduce manual work, partner with researchers and engineers, and evolve infrastructure toward scalable, maintainable patterns.

Lead design of data center power architecture (up to ~50MW) from utility interconnection to IT load. Own reliability philosophy, substations, MV/LV distribution, DER/BESS/PV integration, protection/control, FMEA, studies, commissioning oversight, utility interconnection, and lifecycle support across projects and stakeholders.

Build and maintain backend systems for data center networking: implement Go and Python services, design scalable ingestion/transform pipelines across Kafka, Postgres, and Clickhouse, maintain schema versioning and backwards compatibility, create CI/CD workflows, enable fine-grained historical and real-time querying, collaborate on reproducible model training/evaluation pipelines, and optimize performance to meet real-time serving constraints.