Top Data Engineer Jobs in Portugal

Design, build, and maintain ETL pipelines, databases, and data models to process healthcare claims and related data. Ensure data quality, analyze claims data for trends, and produce reports and visualizations for nontechnical stakeholders. Collaborate with policy and analytics teams to translate requirements into data solutions and improve data infrastructure and analytics capabilities.

Lead hands-on data engineering and architecture for a classified on-prem Analytics Core: build ETL/ELT pipelines, clean and model 30 years of multi-modal and geospatial data, integrate ESRI spatial data, establish AI/ML feature standards, enforce DoD-aligned governance, and mentor transitioning staff to operationalize the solution.

The Data Engineer will design and implement data ecosystems, build data pipelines, and ensure data quality while collaborating with stakeholders and utilizing AWS services.

Design and implement end-to-end data solutions on Microsoft Fabric and Azure for insurance datasets. Build ingestion pipelines (batch, streaming, API), Lakehouse architectures, and data models. Enforce governance, security, compliance, and cost/performance optimizations while guiding engineers and stakeholders on architectural best practices.

Hybrid hardware/software engineer responsible for characterizing 4D LiDAR sensors, supporting customer integrations, building production Python/C++ data pipelines, running calibration and field debugging, maintaining ETL for high-volume sensor data, and coordinating data labeling and collection operations.

Own and build the data foundation for an AI sports-performance platform: design data architecture, real-time streaming ingestion, time-series storage, feature store and millisecond feature serving, sport knowledge graph and evaluation/calibration frameworks, ensure tenant-level isolation and provenance, and work closely with domain scientists and AI engineers to deliver trustworthy, production-grade ML infrastructure.

Design, build, and operationalize scalable AI/ML infrastructure and data pipelines. Implement model lifecycle management (MCP), integrate agent frameworks (e.g., LangChain), manage vector DBs and feature stores, enable HITL workflows, maintain data architectures, mentor junior engineers, and present work internally and externally.

Leads end-to-end data engineering solutions across multiple client engagements, from discovery and architecture through production support. Designs and optimizes Snowflake data platforms, models, warehouses, ELT/ETL pipelines, APIs, integrations, and deployments. Provides technical leadership, client communication, estimation, governance, performance and cost management, engineering standards, mentoring, training, and production escalation support.

Designs and optimizes SQL and dbt transformation pipelines, scalable data models, semantic layers, and reusable business metrics. The role uses dimensional modeling, Data Vault 2.0, and Anchor Modeling across Snowflake, Databricks, and Azure. It partners with stakeholders to establish consistent, high-quality single-source-of-truth data, supports BI and future machine learning use cases, and follows Git-based development, testing, cataloging, lineage, and code-review practices.

Build and maintain data pipelines, warehouses, transformation workflows, data models, and reporting layers. Improve data quality, governance, reliability, performance, and cost efficiency across analytics systems. Manage ingestion and event-streaming workflows, develop star-schema data marts, and collaborate with analysts and stakeholders to translate business needs into scalable data solutions.

Designs and deploys scalable data pipelines, preprocessing workflows, feature-engineering services, and machine learning models for secure DoD environments. The role supports structured and unstructured mission data, exploratory analysis, visualization, model inference APIs, reproducible MLOps workflows, and decision-support capabilities. Responsibilities include collaborating with product, software, platform, DevSecOps, data science, and mission teams; deploying containerized services; participating in Agile delivery; and maintaining technical documentation.

Design, develop, deploy, operationalize, and maintain enterprise-scale data applications, pipelines, and platforms. Process structured and unstructured data, build scalable ETL and ELT workflows, convert data into usable formats, and support monitoring and operation of data platforms. Collaborate with analysts, developers, engineers, and data consumers in an agile environment to deliver mission-driven solutions.

Develop and enhance Citi’s Regulatory Reporting Hub using Java, J2EE, Spring, big data technologies, and JavaScript. Responsibilities include translating business requirements into technical solutions, designing architecture, implementing data reconciliation processes, defining testing strategies, managing UAT, supporting production, improving code and processes, and mentoring junior engineers. The role also involves stakeholder coordination, project status reporting, and delivering reliable regulatory and financial reporting applications.

Designs and manages large-scale structured and unstructured data pipelines in AWS. Builds RAG pipelines involving document ingestion, embeddings, indexing, and retrieval; orchestrates ETL/ELT workflows with Prefect and Apache NiFi; and optimizes Elasticsearch systems. The role supports analytics, ML, and application workloads while ensuring data quality, governance, lineage, security, observability, and reliability. Collaboration with architecture, ML, and application teams and troubleshooting distributed systems are also required.

Designs and maintains scalable data pipelines using Databricks, Spark, and cloud services. Builds transformation workflows, integrates APIs, databases, and cloud storage, and supports analytics and reporting. Implements data validation, monitoring, observability, governance, security, and automation. Collaborates with data science, analytics, and business teams to deliver reliable data solutions in AWS and other cloud environments.

Own the architecture and operation of large-scale autonomous-driving datasets, from multimodal vehicle-data ingestion through curation, quality monitoring, labeling, versioning, and ML training delivery. Design schemas, storage, query, distributed pipelines, observability, and reproducible dataset splits. Lead data-quality, drift, anomaly, auto-labeling, human-review, and closed-loop workflows, including trajectory preparation for imitation learning and offline reinforcement learning. Provide staff-level technical leadership across autonomy, annotation, storage, governance, and model teams.

Build strategic data infrastructure roadmaps, design and implement complex ETL/ELT pipelines, and deliver scalable, secure data solutions. Collaborate across teams on cloud platform selection, data management, governance, privacy, and compliance. The role requires expertise in Databricks, Snowflake, data modeling, performance optimization, and pipeline automation.

Develop and maintain large-scale distributed, API-driven systems and data platforms. Build data ingestion, quality, governance, observability, diagnostics, and automation solutions. Develop AI-powered agents and workflows, collaborate with Product, Research, and Data teams, and deliver scalable software using C#, .NET, SQL Server, AWS, React, and related technologies.

Lead electrical engineering for data center and high-performance AI factory projects. Serve as an electrical subject matter expert, develop studies and specifications, coordinate medium to large projects, provide technical reviews and quality assurance, advise clients, and mentor engineering staff. Responsibilities include design of power distribution and backup power systems, including 400VDC, 800VDC, and 1500VDC systems, with travel required.

Leads mechanical engineering for medium- to large-scale data center projects, overseeing multidisciplinary teams, technical designs, quality, budgets, schedules, client coordination, contractor discussions, field verification, construction issue resolution, and staff development. Produces plans, specifications, drawings, and models for HVAC, cooling, piping, plumbing, fire protection, and related systems while supporting proposals and project travel.

Serve as the electrical subject matter expert for data center and AI factory projects. Lead complex engineering project planning, design, coordination, technical reviews, quality assurance, client engagement, and commissioning support. Develop studies and specifications, advise clients, manage discipline quality procedures, and mentor junior engineers. Travel is required.

Designs, builds, and maintains real-time and near-real-time data ingestion pipelines using Apache NiFi, REST APIs, and scripting. Ensures reliable cross-domain data transfers, data quality, observability, security, and compliance. Parses and transforms structured and unstructured data, develops monitoring and alerting automation, documents system configurations, and collaborates with data, platform, software, security, and governance teams. The role is on-site in Honolulu and supports mission-critical operational systems.

Designs, builds, and maintains real-time and near-real-time data ingestion pipelines using Apache NiFi, REST APIs, scripting, and streaming technologies. Monitors data quality, pipeline health, observability, reliability, and performance while moving classified data across security domains. Develops automation for validation and alerting, documents data flows and procedures, and collaborates with engineering, platform, analytics, security, and governance teams to ensure compliant, trustworthy data delivery.

Develop and maintain large-scale, cloud-native data services and distributed pipelines for multi-tenant healthcare systems. Responsibilities include data modeling, database component development, SQL programming, performance tuning, testing, deployment, code reviews, proof-of-concepts, and full software development lifecycle ownership. Collaborate with global engineering teams, evaluate technologies, apply security and operational requirements, and use AI tools to accelerate development.

Lead data engineering projects by designing scalable data solutions, pipelines, ETL processes, cloud-native applications, and ML-enabled analytical tools. Responsibilities include architecture design, code reviews, CI/CD, documentation, mentoring engineers, client engagement, proposal support, and collaboration with consulting teams. The role requires strong Python, SQL, cloud, big-data, orchestration, and DevOps expertise, with international client travel as needed.