Top Data Engineer Jobs in Portugal

Design and maintain data pipelines, data contracts, and transformation layers for analytics. Model complex sources, enable observability and lineage, collaborate with product teams, and optimize data structures for scalable cybersecurity and industrial datasets.

Design, build, and maintain large-scale data pipelines and DAGs (Airflow) that process imagery, LiDAR, and other sensor data. Improve platform reliability, observability, resource tuning, and Kubernetes deployments. Collaborate with ML, hardware, and full-stack teams; own pipeline design, implementation, testing, and operations in a hybrid NYC role.

Design and implement data platforms, manage data infrastructure, develop streaming architectures, improve performance, and ensure data compliance.

Design, build, and maintain large-scale data pipelines and feature engineering workflows to support fraud and cyber-attack detection models. Improve model deployment, monitoring, drift detection, and MLOps automation while partnering with data scientists, engineers, and product teams to productionize AI solutions and enhance operational reliability and performance.

The Cloud Data Engineer designs and supports scalable Snowflake and Azure data architectures, environments, and ETL/ELT pipelines. Responsibilities include Snowflake performance and cost optimization, Azure resource management, security controls, troubleshooting, documentation, design reviews, and collaboration with architecture, engineering, BI, and security teams. The role also contributes to software development, testing, debugging, mentoring, and data warehouse and data mart implementation.

Design, build, maintain, and optimize Spark and Scala ETL/ELT pipelines on AWS for terabyte- and petabyte-scale datasets. Work across S3, Snowflake, Kafka, and monitoring systems, resolve production data-quality and performance issues, write automated tests, participate in architecture and code reviews, and support on-call operations. Use generative AI to improve pipeline development, monitoring, and engineering productivity.

Designs, develops, tests, deploys, and supports batch and streaming data pipelines using Azure and Databricks. Builds ETL/ELT processes, optimizes data workflows, supports cloud modernization, and performs monitoring, troubleshooting, and root cause analysis. Collaborates with business and technical teams on requirements, data governance, lineage, and audits. Mentors junior engineers and communicates solutions to technical and non-technical stakeholders.

Build and maintain scalable production data pipelines, infrastructure, warehouse models, analytics platforms, and data-quality systems. Partner with software engineers to instrument product features and ensure reliable event data. Support Hex and Snowflake self-serve analytics, maintain business metrics and data logic, and develop monitoring, validation, alerting, and observability tooling. The role also collaborates with product, analytics, marketing, and engineering teams, with potential future exposure to recommendation and LLM-based product work.

Design, develop, and modernize secure enterprise applications supporting Intelligence Community missions. Build Java or Python backend services, RESTful APIs, Angular interfaces, distributed data processing and search capabilities. Collaborate on architecture and requirements, lead technical design discussions, conduct code reviews, troubleshoot complex issues, and improve performance and scalability. Contribute to CI/CD, automated testing, and DevSecOps initiatives in an Agile environment.

Build and maintain scalable data pipelines and datasets for ML/AI workflows; collect, clean, and preprocess structured and unstructured data; ensure data quality, availability, governance, and security; collaborate with data scientists and ML engineers; optimize storage and troubleshoot pipelines.

Design and scale semantic data and AI infrastructure, including embedding pipelines, knowledge graphs, ontologies, vector and hybrid retrieval, RAG systems, and LLM-powered applications. Build production-grade APIs and data pipelines, optimize private GPU inference, establish evaluation and reliability frameworks, and ensure explainability, attribution, and safe outputs. Collaborate across product, analytics, data engineering, and ML teams while mentoring engineers and translating business needs into grounded AI systems.

Provides cybersecurity and systems engineering support across multiple networks and security domains. Responsibilities include SIEM data-flow monitoring, event and log management, configuration management, system maintenance, root-cause analysis, security patching, compliance activities, infrastructure engineering, testing, integration, and documentation. The role requires maintaining highly available services, resolving escalated issues, coordinating maintenance, and supporting secure infrastructure across Intelligence Community environments.

Supports network and cybersecurity services for Intelligence Community systems across multiple networks and security domains. Responsibilities include SIEM data-flow monitoring, event and log management, configuration management, compliance and identity monitoring, system maintenance, troubleshooting, root-cause analysis, vendor revision engineering, testing, integration, documentation, and infrastructure security. The role requires advanced systems engineering, Linux, networking, virtualization, cloud, and SIEM expertise while maintaining high service availability.

Build scalable data processing applications, ETL/ELT pipelines, AWS-based data solutions, and analytics integrations. The role involves optimizing high-throughput systems, supporting engineering analysis and optimization, working with structured and unstructured data, and collaborating across engineering teams. Candidates need a bachelor’s degree in engineering, U.S. citizenship, at least two years of software engineering experience, and proficiency in C# and Python.

Lead development of an AI-ready research data ecosystem for vaccine R&D: design integrated data architectures, automate ingestion and transformation pipelines, define semantic/metadata frameworks, build knowledge graphs and RAG systems, and develop multimodal predictive and translational ML models. Provide technical leadership, mentor teams, and collaborate across scientists, bioinformatics, and enterprise data organizations to accelerate AI-driven vaccine discovery and decision-making.

Lead architecture and standards for CoreWeave's enterprise data ecosystem: design lakehouse/streamhouse architectures, modeling and semantic layers, governance, data quality, lineage, observability, and reusable data products. Drive cross-domain solutions, resolve performance and scalability constraints, evaluate core data technologies, conduct architecture reviews, and mentor senior engineers.

Design, build, and operate instrumentation, DAQ, and automated test control systems for spacecraft testing. Develop test automation (LabVIEW, Python, MATLAB), commission and calibrate sensors, troubleshoot hardware/software integration, perform post-test data analysis, and maintain data management and requirements traceability in hazardous test environments.

Lead the development of healthcare applications and data systems, focusing on audience intelligence and compliance. Design scalable data pipelines, APIs, and reporting systems while ensuring high data quality and security in regulated environments.

Configure, integrate, and deploy the BT tool stack (Snowflake, Salesforce, Streamlit, workflow tools). Build integrations and Streamlit apps, deploy AI-enabled automations, maintain Snowflake data models and reports, catalog assets with DataHub, implement SDLC/testing/guardrails, ensure data security, and partner with Engineering/InfoSec while mentoring BT team members.

The Lead Software Engineer will build healthcare applications and data systems focusing on audience intelligence, while leading development of scalable infrastructure and ensuring compliance with privacy regulations.

Lead architecture and hands-on engineering to design, scale, and govern a cloud-native lakehouse using Databricks and Microsoft Fabric. Build batch/streaming pipelines, ensure HIPAA-compliant PHI handling, produce analytics-ready datasets, mentor engineers, and drive platform strategy, governance, and reliability.

Lead infrastructure strategy and build/automate AWS infrastructure. Maintain and grow data lakehouse (Databricks) and event processing. Champion security, CI/CD, monitoring, model serving, and provide engineering leadership while participating in L2 support rotation.

Responsible for building data models, developing ELT pipelines, implementing data quality checks, and utilizing best practices in data engineering and healthcare analytics.

Designs, builds, and maintains secure cloud data pipelines and centralized repositories; publishes curated datasets; develops WPS AI agents; produces dashboards and visualizations for senior military leadership; supports NATO and annual statutory reporting and prepares technical briefings and deliverables.

Build and maintain ingestion pipelines for heterogeneous healthcare data (TPA feeds, claims, eligibility, enrollment). Design dbt models and orchestration (Dagster/Airflow), implement data quality monitoring and observability, and partner with data science to produce and maintain feature pipelines and feedback loops.