Top Data Engineer Jobs in Portugal

The Senior Geospatial Data Engineer will design and deliver geospatial data pipelines, manage data lakes, develop analytical environments, and integrate geospatial tools.

As a Data Engineer, you will develop data-driven decision analysis products for the DoD, ensuring effective stakeholder engagement, and leveraging advanced analytics and machine learning techniques.

The Data Engineer will develop data-driven decision analysis products, provide analytic consulting, support stakeholders with tools, and optimize defense systems for national security.

As a Founding AI/Data Engineer, you'll design and build AI-driven products, collaborate across teams, and ensure system reliability while enhancing user experiences.

The Data Integration Lead designs and manages data ingestion pipelines, ensuring data integrity and security while supporting ETL processes in classified environments.

Lead technical strategy and implementation of V-BAT fleet data analysis pipelines and tooling. Transform raw flight, simulation, and production data into metrics, dashboards, and reports; perform fleet-wide studies, anomaly investigations, and root-cause analysis; partner with cross-functional teams and mentor engineers on analysis best practices.

Develop and implement large-scale Big Data solutions using Java, Hadoop, NoSQL, and MPP technologies. Design and optimize distributed, data-intensive systems, participate in architecture discussions, collaborate with senior architects and offshore teams, and deliver high-quality projects. Engage with clients, conduct technical sessions, create documentation and case studies, and share knowledge across the organization.

Lead Data Engineer responsible for building, optimizing, and operating secure, scalable data pipelines and platforms. Develop and run batch and streaming pipelines, workflow orchestration (Airflow), SQL-based transformations, and production-grade Python/PySpark code. Collaborate with analysts and data scientists, own system reliability and security, mentor junior engineers, and apply enterprise-authorized AI tools with strong validation and data sensitivity practices.

Design, build, and maintain cloud-based data pipelines and data products across AWS, Azure, or GCP. Advise clients on cloud data architectures, implement production data solutions, and collaborate with users, developers, and analysts to maximize data value.

Design, build, and maintain cloud-based data pipelines and data architecture on AWS/Azure/GCP. Advise clients on cloud ingestion and processing, collaborate with stakeholders, and deliver production-ready data products using modern data tools.

Design, build, and maintain cloud data pipelines and data products across AWS, Azure, or GCP. Advise clients on cloud data architecture, implement production database and ETL/streaming solutions, collaborate with stakeholders, and evaluate architectural tradeoffs to meet business needs.

Design, build, and maintain cloud data pipelines and architectures on AWS/Azure/GCP. Advise clients on cloud ingestion/processing strategies, implement production data products, collaborate with stakeholders, and evaluate architectural tradeoffs.

Design, build, and maintain cloud data pipelines and data architecture on AWS, Azure, or GCP. Advise clients on cloud ingestion and processing strategies, collaborate with stakeholders to maximize data value, and deliver production data products using modern databases, ETL/scripting, and engineering best practices.

Design, build, and maintain cloud-based data pipelines and architectures on AWS/Azure/GCP. Advise clients on cloud data strategies, collaborate with stakeholders, implement production data products, and articulate architectural trade-offs.

Design, build, and maintain cloud-based data pipelines and architectures on AWS, Azure, or GCP. Advise clients on cloud data solutions, implement production data products, collaborate with stakeholders, and evaluate architectural trade-offs to meet business needs.

Design, build, and maintain cloud data pipelines and data architecture on AWS/Azure/GCP. Advise clients on cloud-based ingestion and processing, collaborate with stakeholders, and deliver production-ready data products while evaluating architectural trade-offs.

Build and maintain production data pipelines and models using SQLMesh, BigQuery, and Python. Improve observability, reliability, and performance; support finance and revenue pipelines; participate in on-call rotation and own features end-to-end.

Design, build, test, and support cloud-based data engineering solutions: ETL pipelines, data workflows, APIs, and data services. Deploy and troubleshoot in Linux/cloud environments, collaborate with platform and DevSecOps teams, ensure secure coding, document data flows, and support mission-driven programs.

Build and maintain data pipelines using Python and Spark/PySpark. Work with Presto/Athena and Airflow to collect, aggregate, and store data powering BI. Emphasizes strong algorithms, data structures, and shipping high-quality software.

The Data Engineer/ETL Engineer will support cloud-based and on-prem application development, focusing on data management and analytics for defense and intelligence.

Lead architecture and delivery of frontier AI solutions: define end-to-end technical designs, establish reusable AI engineering patterns, guide platform integration and production readiness, advise cross-functional stakeholders, and ensure secure, scalable, observable AI products that are commercially viable.

As a Data Engineer, you will create and optimize datasets and data pipelines, focusing on large-scale data collection across various modalities and collaborating with multiple teams.

The AI-Native Data Engineer will build data pipelines, architect databases, design GCP infrastructure, and automate workflows for energy management using AI.

Develop and design data pipelines, optimize data delivery and automate processes to support end-to-end solutions in various settings.

As an AWS Data Engineer, you will develop data pipelines, create data models, troubleshoot issues, and collaborate with teams while utilizing tools like PySpark and SQL.