Top Data Engineer Jobs in Portugal

As a Data Engineer, you'll create and maintain data pipelines, optimize data architecture, and support analytics tools for performance insights.

The Data Engineer will build and scale Baseten's internal data platform, designing data models and pipelines while enabling self-service analytics and ensuring data reliability.

As a Data Engineer, you will build and maintain data pipelines, ensure data quality, support ML workflows, and optimize query performance using various technologies.

Develop and maintain data infrastructure for safety data analysis, build scalable data pipelines, conduct exploratory analyses, and support regulatory reporting in AV safety.

The Data Engineer is responsible for designing data workflows and pipelines, implementing systems engineering principles, and deploying data streaming technologies while ensuring compliance with industry regulations and best practices.

The Technical Service Data Engineer translates engineering specifications into precise repair procedures within the ERP, utilizing CAD and ensuring data accuracy throughout engineering changes.

The Data Engineer will build and maintain data pipelines, optimize AI workflows, and ensure data operations, governance, and security for strategic intelligence.

The role involves SQL and data analysis to troubleshoot issues, with 8+ years of required experience. Experience with C# and scripting tools is preferred.

Design and build Starlink's commercial operating system by identifying go-to-market bottlenecks, architecting scalable systems and AI-powered workflows, integrating CRM and data platforms, improving commercial data quality, and enabling data-driven decision-making to drive revenue and operational efficiency.

Build and maintain production data pipelines and models to support analytics, ML, and research. Ensure data quality and availability, operate and monitor the data platform, investigate failures, optimize performance and costs, and collaborate with Product, Engineering, and Research teams.

Design, implement, and optimize scalable data pipelines and infrastructure on AWS. Maintain ETL artifacts, provide Tier 3 support, collaborate with stakeholders and a product team, document dataflows, and occasionally support off-hours deployments.

As a Data Engineer, you will design, build, and maintain data pipelines and workflows, transforming raw data sources into clean, reliable data streams for healthcare clients.

The data engineer will build and maintain data pipelines, implement data models, write quality checks, configure tooling, and resolve pipeline issues.

This role offers training for aspiring Data Engineers, focusing on technology of choice, interview preparation, and skill enhancement with guidance on OPT STEM extension.

As a Snowflake Data Engineer, you will design and maintain scalable data pipelines, optimize SQL transformations, and support analytics platforms, collaborating with stakeholders.

Design and maintain scalable ETL/ELT pipelines, data integrations, APIs, databases, warehouses, and workflow orchestration. Improve data quality, security, governance, reporting accessibility, and infrastructure reliability across a multi-location organization. Collaborate with analysts, technology teams, and business leaders, troubleshoot complex data issues, support CI/CD deployments, and provide technical leadership and mentorship while shaping long-term data strategy.

Maintain and extend production Python applications, build internal tools and reports, and own the Power BI reporting estate. Support SQL Server reporting databases, desktop estimating and pricing tools, and scheduled system automations. Gather requirements from business departments, follow version control and code review standards, document systems, and gradually assume independent ownership under senior technical guidance.

Lead end-to-end data architecture and engineering for scalable AI and analytics systems. Define standards for data modeling, ingestion, transformation, quality, governance, security, and observability. Mentor data engineers, lead complex projects, collaborate with AI/ML and software teams, translate stakeholder needs into technical designs, and drive data-driven innovation across the organization.

Build distributed data systems for petabytes of video, lidar, and telemetry data. Responsibilities include developing multimodal data lake storage, query engines with indexing and vector search, and high-throughput dataloading pipelines delivering data to GPUs. The role involves optimizing distributed storage and compute, query planning, streaming computation, zero-copy data flow, and real-time indexing for robotics and Physical AI applications.

Lead design and implementation of enterprise-scale data architectures, pipelines, and integration frameworks supporting ontologies, knowledge graphs, and Semantic Web technologies. Build and optimize ETL/ELT processes for structured and unstructured data, enable cloud/containerized deployments, ensure data quality, lineage, governance, and support AI/ML initiatives. Provide technical leadership, documentation, automated monitoring, and mentorship to Government stakeholders and project teams.

Design and implement Palantir Foundry applications and data pipelines for defense clients. Ingest, transform, and model data; integrate AI/ML where applicable; implement CI/CD and DevSecOps practices; collaborate with stakeholders to translate requirements into technical solutions; support analytics, application, and workflow development in Foundry.

Designs, develops, and maintains backend services and data pipelines for a scalable data platform. Writes production Python and SQL, architects storage and processing solutions, leads technical decisions and cross-functional initiatives, troubleshoots production issues, reviews code, mentors engineers, and collaborates with data science, product, and engineering stakeholders.

Designs, builds, and maintains cybersecurity log collection, management, and SIEM environments across on-premises and cloud systems. Responsibilities include configuring data pipelines, troubleshooting data flow, storage, and display issues, performing root cause analysis, maintaining uptime and versions, improving processes with automation, documenting systems, training team members, and supporting customers. The role requires occasional on-call work and collaboration across project phases.

Designs, builds, and operates scalable data platforms and ELT pipelines across Google Cloud using dbt, Python, Airflow, and BigQuery. Responsibilities include data modeling, governance, security, cost optimization, observability, infrastructure as code, incident response, and end-to-end feature delivery. The role pilots AI-assisted engineering practices, develops reusable tooling, collaborates with business and technical stakeholders, and mentors data engineers.

Design and build scalable pipelines and evaluation frameworks to compute driving-performance metrics across fleet and simulation data. Perform deep analysis of time-series, event, and geospatial data to identify regressions and root causes. Build geospatial analytics, release gating tooling, and LLM-powered agentic workflows to triage issues and propose fixes. Collaborate with engineering teams and adhere to QMS processes.