Top Data Engineer Jobs in Portugal

The Sr. Data Engineer is responsible for database design, development, performance monitoring, and data analytics to support business needs and improve data management.

The Sr. Data Engineer is responsible for application development, database performance monitoring, data analytics, and ensuring compliance with quality standards.

The role involves database application development, performance monitoring, data analytics, and ensuring compliance with quality standards. The engineer will develop data architecture and mentor peers on data management best practices.

The Network/Data Engineer will primarily assist with F5 load balancer implementation projects and must have experience with large IP networks and network protocols. Responsibilities include new network elements turn up, network upgrades, and configuration deployments.

The Data Engineer will design and maintain data pipelines, optimize cloud data warehouses, and collaborate with analytics teams while mentoring junior staff.

The Data Developer will focus on mid-tier and backend development, primarily using C# and PL/SQL in a financial context.

Design, develop, and monitor large-scale cloud-native data solutions and ETL pipelines; support ML model deployment, ensure code hygiene and CI/CD, mentor engineers, produce documentation and runbooks, and engage with clients to deliver analytics-driven solutions.

Build and maintain data platform and production data warehouse; translate PM and quant requirements into technical solutions; design ETL, data modeling, cleansing, monitoring, and alerting systems; evaluate new tooling; optimize performance and manage vendor relationships.

The AWS Cloud Data Engineer will design, develop, and enhance AWS data environments, build scalable Data Lake solutions, and lead proofs-of-concepts into production.

Establish and maintain mission operations architecture for a lunar relay satellite and network. Plan, script, and execute training simulations; mentor real-time operators; support operations product development, testing, regulatory documentation, system architecture, interfaces, timelines, and procedures. Develop lessons and procedures for spacecraft subsystems, communications satellites, ground networks, and simulators, while cross-training for real-time mission support.

Design, build, monitor, and optimize scalable ETL/data pipelines on Azure. Collaborate with scientists and engineers to integrate systems, support analytics/ML, and ensure performance, cost-effectiveness, and data governance.

The Data Engineer will design and build solutions for investment insights using big data technologies, developing data pipelines, and collaborating with cross-functional teams.

Build and deploy production-grade LLM applications, AI agents, models, and scalable RAG pipelines for investment and business workflows. Architect secure MCP integrations with enterprise systems, establish MLOps and LLMOps practices, optimize model performance and latency, and develop evaluation, monitoring, governance, and rollback processes. Collaborate with data engineering and platform teams to provide secure, governed access to organizational data.

Design and maintain ingestion pipelines for 835/837 and scanned EOBs: OCR, LLM-assisted extraction, integrations (SFTP, clearinghouses), data modeling, validation, and reconciliation to produce deterministic, trustworthy healthcare records.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.

As a Staff Data Engineer, you'll oversee Gamma's data infrastructure, architect scalable systems, mentor engineers, and drive strategic decisions for data usage across the organization.

Lead and mentor multiple Databricks-focused data engineering teams, define engineering best practices and reusable frameworks, drive CI/CD and performance/cost optimization, build and support analytical and streaming pipelines, and collaborate with architects, product owners, and cross-functional partners to deliver high-quality data products.

Looking for a Big Data/Scala Developer to build large scale applications using Scala, Spark, and Hadoop in a collaborative agile environment.

The Big Data Developer (Spark) will be responsible for Spark and Scala development, Hadoop performance tuning, and SQL coding. Requires extensive experience in data processing and performance optimization.

Own end-to-end data labeling pipelines and vendor relationships, build annotation tooling and dataset browsers, define labeling taxonomies and QC standards, partner with researchers to design data collection strategies, monitor dataset metrics, integrate new data sources, and close the loop from labeled data to model improvement.

Lead architecture and implementation of scalable ML data pipelines and tooling to turn autonomy data into training datasets. Build data selection, active learning, inference-at-scale, vector DB management, labeling integration, QC automation, and introspection tools while partnering with ML researchers and infra teams.

Design, build, and operate cloud and edge data pipelines for robotic systems. Manage large multimodal datasets, implement on-device capture (MCAP/Protobuf), automate MLOps/DataOps workflows, ensure data quality, and build tools for debugging, experimentation, and production deployments across AWS and edge devices.

Manage administration, disaster recovery, network design, and project management while providing application and integration support. Collaborate on system design and participate in discussions for optimal solutions.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from varied sources. Work with event-driven and batch architectures, implement authentication and integration patterns, ensure observability/monitoring, optimize data flows for cost and performance, and collaborate with product, infrastructure, and engineering teams to onboard and maintain data sources at scale.

The Data Processing Engineer will architect and enhance data read/write capabilities for a data processing engine, focusing on large-scale data, performance optimization, and collaboration with engineering teams.