Top Data Engineer Jobs in Portugal

The Lead Data Engineer designs and oversees data systems to facilitate data-driven decisions, collaborating with teams to build scalable data infrastructure and tools.

Design and implement scalable LLM- and RAG-based systems integrating knowledge graphs and multi-omics data, build agentic orchestration and conversational AI, collaborate with data engineering and experimental scientists, and deploy pipelines that synthesize biological information to support therapeutic discovery.

Design and operationalize data architectures, instrumentation, and analytical frameworks to support SEO and AI-driven discovery. Partner with data engineering and BI to build reliable datasets, monitoring, and automation. Prototype and productionize LLM-based workflows and agent-like systems, translate marketing needs into scalable decision systems, and document assumptions and processes.

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.

Provide Level 1 support and daily operations for critical data pipelines, including validation, cleaning, incident management, reporting, tooling, documentation, and permissions/entitlements support for finance trading systems.

Build and productionize internal AI-powered tools and data systems. Implement and maintain infrastructure, data pipelines, deployments, monitoring, and access controls. Integrate third-party AI services, ensure data quality, document systems, and collaborate with stakeholders to deliver maintainable solutions.

The role involves developing and integrating cloud-native data services and APIs, supporting data transformation, and maintaining backend services using AWS technologies.

The Senior Software Engineer will scale open-source data infrastructure, handle data lifecycle tasks, and support internal and external products.

Lead design and implementation of batch and streaming data pipelines, build data models, implement data quality and testing, manage orchestration and IaC, mentor engineers, and communicate technical direction and tradeoffs to stakeholders.

As a Software Engineer on Glean's Data Foundations team, you'll build and scale data ingestion connectors, transforming unstructured content into structured data while ensuring system reliability and security throughout the data processing pipeline.

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

As a Full Stack Software Engineer, you will develop a scalable data platform, create data pipelines, and collaborate on software solutions for SpaceX's Starlink program.

Develop and enhance the data infrastructure for Waymo's ML models, focusing on data needs, storage efficiency, and integration across various use cases.

As a Senior Software Engineer on the Observe team, you will own the streaming data product surface, design APIs, and lead technical direction, ensuring the effective handling and querying of unified telemetry data at scale.

As an AI/ML Engineer and Data Scientist, you'll analyze data, develop predictive models, and provide insights to clients across various sectors, using advanced statistical techniques and machine learning tools.

As a Senior Software Engineer, you will develop distributed data storage and processing systems, enhance performance, and support diverse data workloads at Databricks.

Develop next-gen distributed data storage and processing systems, enhance query performance, and support diverse workloads from ETL to data science.

As a Staff Software Engineer at Databricks, you will develop distributed data storage and processing systems, focusing on projects like Apache Spark, Delta Lake, and performance optimization for diverse data workloads.

Design, evolve, and maintain large-scale ETL/ELT pipelines, data warehousing, and monitoring. Collaborate with internal stakeholders, implement CI/CD and Airflow orchestration, ensure security/RBAC and scalability, and improve BI dashboards and data governance.

The Staff Engineer will design and maintain data products, lead projects, mentor engineers, and optimize data pipelines while collaborating across teams using Agile practices.

The Sr. Data Engineer will build and manage data pipelines for large datasets, collaborate with teams, and leverage cloud technologies for data processing.

Lead Data Engineer responsible for defining architecture, engineering standards, and best practices for the enterprise data platform, collaborating with distributed teams for modernization and scalability.

Design and operate petabyte-scale end-to-end data pipelines for autonomous driving: onboard upload, cloud preprocessing, dataset production, and model training input. Build data cleaning, annotation QA, lineage, versioning, metadata management, and high-throughput distributed processing. Optimize I/O, memory, transmission, and containerized deployments; support cross-team collaboration and algorithm iteration.

Design, implement, and maintain scalable Data Lake architectures; integrate Data Lake with Stardog knowledge graph; optimize ETL/ELT and Delta Lake pipelines; enforce DoD IL-4/IL-5 security, IAM/RBAC, and Unity Catalog governance; produce compliance and performance reports; support DevSecOps, CI/CD, and cloud integrations across AWS/Azure/GCP.

Build, enhance, and sustain Army applications integrating AI-enabled analytics and Vantage; perform data mining, preprocessing, and modeling; develop and maintain Microsoft 365 SharePoint sites, manage permissions across SharePoint/Qlik/Power Apps, refine data governance artifacts, and support verification, validation, and user issue resolution.