Top Data Engineer Jobs in Portugal

Build and improve Radar's data infrastructure with a focus on customer feedback and successful implementation. Engage with customers to enhance their experience and deploy new solutions.

Lead Data Engineer designs, develops, tests, implements, and supports cloud-based data solutions. Collaborates with agile teams, mentors engineers, builds streaming and batch pipelines using big-data and cloud technologies, and ensures performant, well-tested code.

As a Sr. Lead Data Engineer, you'll collaborate across teams to develop technical solutions, lead developers, and utilize big data technologies and cloud services to support data transformations.

Own and operate the iMData platform: design and build Databricks-based ETL pipelines using PySpark and medallion architecture, create gold-layer star schemas, migrate assets from Synapse to Databricks, implement CI/CD and Terraform IaC, ensure data security and observability, mentor junior engineers, and collaborate with stakeholders and ML engineers to deliver production-grade analytics and AI-ready data.

Lead design and standards for how R&D data is sourced, stored, governed and served for analytics. Assess and remediate data architectures, translate business needs into data/technology requirements, guide data migration design and implementation, and advise on on-premise and cloud data infrastructure for the analytics ecosystem.

Design, build, and scale the Veza Access Graph backend: develop graph features, improve performance, reliability, and APIs, collaborate cross-functionally, and implement monitoring, logging, and compliance capabilities for identity and access management at scale.

Lead Data Engineer will design, build, test, and support cloud-based data solutions and streaming systems. Collaborate with Agile teams and product managers, mentor engineers, implement big data tooling (Spark, Kafka, EMR), and optimize data warehousing (Redshift, Snowflake) using Java/Scala/Python and SQL. Ensure code quality with unit tests and reviews.

Lead Data Engineer designs, builds, tests, and supports cloud-based data platforms for marketing and messaging. Collaborates across Agile teams to deliver scalable, real-time data and ML-enabled solutions using distributed systems, data warehousing, ETL, and streaming technologies. Mentors engineers and participates in code reviews and performance tuning.

Lead Data Engineer designs, develops, tests, and supports cloud-based data solutions. Collaborates with Agile teams on distributed, real-time, and ML-enabled systems using languages and data platforms (Java, Scala, Python, Go, Redshift, Snowflake). Mentors engineers, performs code reviews and unit tests, and drives technical innovation and experimentation.

Lead design and delivery of scalable, secure cloud data pipelines and products. Translate requirements into architecture, apply advanced data modeling (Data Vault 2.0/dimensional), embed data quality, observability, security, and DataOps/CI-CD practices, optimize performance and cost, mentor engineers, and enable AI/ML-ready datasets within an agile DevSecOps model.

Design, build, and operate scalable cloud data pipelines and platforms (Azure preferred). Implement DevSecOps, CI/CD, automated testing, monitoring, performance tuning, and production readiness. Mentor engineers, drive operational excellence, and translate requirements into robust technical designs. Apply healthcare domain knowledge and collaborate in agile teams to deliver secure, reliable data products.

Design, build, and maintain batch and near-real-time data pipelines on Microsoft Fabric and Azure. Ingest, transform, and curate raw source data into analytics-ready tables, semantic models, and Power BI datasets. Ensure data governance, security, observability, and cost-efficient ELT/ETL workflows. Troubleshoot data quality and pipeline issues, document architecture and lineage, and collaborate with stakeholders to deliver reliable data products.

The Data Engineer will design, develop, and deploy scalable AI-enabled data solutions, implement machine learning models, and conduct data analysis in the DoD's CDAO ADA IR program.

Develop, maintain, and optimize data integration pipelines, API services, and front-end interfaces for geospatial and structured data. Build scalable, secure web applications and metadata-driven search for ESRI GIS platforms and Unity Catalog. Implement RESTful/GraphQL APIs, manage CI/CD and Kubernetes deployments, ensure API authentication, and optimize queries/indexing for large-scale geospatial datasets.

As a Senior Data Engineer, you will design and develop AI-powered data solutions, investigate tools, and collaborate with engineering to enhance Sleuth's platform.

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

The Data Engineer will build and maintain data platforms, deploy pipelines, monitor transformations, and collaborate with Data Scientists and DevOps.

The Full Stack Data Engineer will develop and maintain data pipelines, optimize storage strategies, integrate APIs, and ensure compliance with security frameworks for a DoD contract.

As a Data Engineer, you will optimize data pipelines, develop code in Python and Spark, manage cloud infrastructure, and drive data solutions.

The Data Engineer designs data architectures and pipelines, supports analytics teams, solves complex data challenges, evaluates tools, and mentors team members.

As a Data Engineer, you will manage data pipelines, automate processes, and collaborate on software solutions to optimize supply chain performance.

As a Data Engineer at SpaceX, you'll develop metrics and tools to assess the scaling and efficiency of the Starlink network, collaborating with various teams.

The Senior Geospatial Data Engineer will design and implement cloud-based geospatial data infrastructures, optimize data processes, and lead project collaborations within the team.

The Principal Software/Data Engineer will develop and enhance software systems, ensuring adherence to design requirements, and provide input on system designs, with significant experience in software engineering and clearances required.

Lead the design and optimization of batch and streaming data pipelines, ensuring high-quality data delivery for AI and analytics, while mentoring and promoting engineering best practices.