Top Data Engineer Jobs in Portugal

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.

Design, build, and maintain Master Data Management (MDM) data integrations and data quality flows. Define standards for scalability, security, error handling, and auditing. Estimate and scope implementations, produce technical specifications, implement DevOps for integrations, participate in testing, support offshore/third-party teams, and drive continuous improvement for MDM solutions.

Design, build, and maintain systems and architecture to collect, store, and analyze large volumes of data in support of DoD/IC programs. Work with stakeholders to enable data ingestion, storage, and analytics pipelines.

Design, build, and maintain scalable data pipelines and models for Finance and operations; collaborate with analysts and data scientists to provision trusted analytics; ensure governance, performance, testing, and incident root-cause fixes; recommend technologies and mentor team members to adopt cloud-first, best-practice data architectures.

Design and own the companys end-to-end data and analytics stack: build metrics, dashboards, and reporting; instrument product and GTM signals; transform messy data into structured inputs for AI agents; and define analytics infrastructure (dbt, Snowflake, Mode) while partnering across founders, engineering, and GTM teams.

As a Data Engineer at Booz Allen, you'll design and develop data pipelines, support data systems, and ensure data security while working in a team-focused environment.

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.

Support the creation of business intelligence tools for the War Research Enterprise by developing scalable data pipelines and governance policies while collaborating with cross-functional teams.

The Data Engineer role involves developing and maintaining data pipelines for forecasting in commercial real estate, ensuring data integrity and supporting analytics teams.

Design, implement, and maintain scalable, secure geospatial database platforms supporting mission-critical Defense and Intelligence systems. Responsibilities include database design, performance tuning, high-availability and disaster recovery, automation, data security, and customer-facing technical guidance across implementation lifecycle.

Design, deploy, and optimize secure, scalable enterprise geospatial database solutions across cloud, on-premises, and hybrid environments. Configure, monitor, tune, secure, and automate databases; support backup/DR and provide technical guidance for migrations and integrations to enable mission-critical ArcGIS-driven systems.

Design, deploy, and optimize secure, scalable enterprise geospatial database environments across cloud, on‑prem, and hybrid infrastructures. Implement backup/recovery, HA/DR, performance tuning, security, automation, and data integration while collaborating with cross‑functional teams to support mission-critical ArcGIS workflows.

Design and implement scalable, secure geospatial database platforms for mission-critical defense and intelligence applications. Collaborate across teams on requirements, build, deployment, HA/DR, performance tuning, security, automation, and migrations to ensure reliable geospatial data delivery.

Design, implement, and maintain scalable, secure geospatial database platforms for mission-critical Defense and Intelligence systems. Tasks include database design, HA/disaster recovery, performance tuning, security and access controls, automation of data workflows, and customer-facing architecture and migration guidance.

Design, implement, and maintain secure, high-availability database solutions across cloud, on-premises, and hybrid environments. Collaborate with cross-functional teams to deploy, tune, automate, and secure mission-critical geospatial data platforms. Provide guidance on database design, migration, integration, backup/recovery, performance optimization, and compliance to support ArcGIS-driven systems.

The Scientific Data Engineer will design data architecture, build ETL/ELT pipelines, implement data quality checks, and develop semantic layers for AI-consumable data products in healthcare research.

Build and maintain production data pipelines and tools for large-scale image and sensor datasets. Design, develop, and test full-stack applications for vector and raster data, implement cloud and edge data offboarding, create continuous delivery pipelines (Kubeflow/Airflow/Databricks), collaborate with cross-functional teams, and document code, APIs, and system architecture.

Design, develop, and maintain data pipelines and software solutions to process and combine diverse data sources. Perform statistical analysis (regression, anomaly detection, clustering), automate and optimize data products, communicate findings to technical and non-technical stakeholders, elicit system requirements, validate performance, and support time-sensitive intelligence operations.

Design, build, and maintain an internal data platform and pipelines. Ensure secure, governed, resilient data access for engineering and BI teams. Partner with architects, implement automations, support platform consumption, mentor users, and drive continuous improvement and compliance.

Lead implementation of ETL patterns and reliable data infrastructure, partner with business and engineering teams to prioritize and deliver integrations, APIs, and reusable components, and support operational data applications in an Agile environment.

Build and operate ML training and serving infrastructure; design, develop, and launch backend systems; collaborate across teams to decompose projects; maintain availability through monitoring and on-call support; review and debug large codebases; contribute to hiring and team growth.

Design, build, and operate scalable batch and real-time data pipelines on Databricks/Azure, implement medallion architecture with Delta Lake, ensure data quality and governance via Unity Catalog, support CI/CD and production operations, and collaborate with stakeholders to deliver analytics-ready datasets for BI and ML use cases.

Design, implement, and maintain Azure-based data pipelines and analytics-ready datasets. Develop transformations, optimize SQL, contribute code across the platform, support production workloads, apply engineering patterns, work with stakeholders, and support CI/CD, testing, and monitoring for analytics and AI/ML use cases.

As a Senior Software Engineer on the Data team, you will build data ingestion tools, support internal teams, and enhance systems for accuracy and reliability.