Top Data Engineer Jobs in Portugal

Design, build, and operate production LLM-driven agents that crawl, extract, and verify web evidence to enrich business identities. Own classification, discovery, linkage, risk scoring, shared agent infrastructure, model/tool selection, prompt engineering, eval methodology, and cost/latency optimizations for real-time enrichment pipelines.

Design and lead spacecraft data and data-handling architectures for Blue Ring satellites. Develop and manage Command & Telemetry and Parameter databases, onboard storage and file management, data uplink/downlink, sequencing, and prioritization. Collaborate with flight software, systems, test, and operations teams to implement, automate, and verify scalable data solutions across a vehicle fleet.

Lead enhancement, integration, and support for IBM InfoSphere MDM and Kafka-based integrations. Develop specs, troubleshoot production, manage deployments (WildFly), automate scripts, run SQL, support CI/CD, collaborate with DBAs and infra teams, and deliver testing, UAT, and monthly application reporting.

As a Level 1 Data Centre Engineer, you will provide hands-on support, troubleshooting, and maintenance for data centre infrastructure, ensuring performance and reliability, while collaborating with technical teams and adhering to safety standards.

Lead and shape the Security Data & AI Lab's data engineering capability: define strategy and roadmap, own scalable cloud-native data pipelines and platforms, embed secure-by-design and engineering best practices (CI/CD, testing, observability), enable production-grade foundations for AI/ML, mentor engineers, and partner across Security, Cloud, Architecture and Product teams.

Lead ownership of data sourcing, modelling, and distribution for compliance and reporting. Define and implement a central data foundation, set standards, ensure data quality, guide teams, and document end-to-end data flows to enable consistent, reusable reporting solutions.

Design and implement AI solutions, focusing on data pipelines, workflow automation, and ensuring security and governance in a production environment. Collaborate to create reliable, scalable models and optimize enterprise data integration.

Build and scale a growth data platform: design queues and workers for enrichment, routing, assignment, and activation; integrate CRM, ads, intent, and enrichment vendors; convert experiments into reusable platform primitives; and debug production issues across Snowflake, dbt, Dagster, AWS, vendor APIs, webhooks, and downstream systems.

Own and iterate on Nerve, a desktop-to-cloud data-collection platform: integrate C#/.NET recorder with Electron, build anti-cheat/fraud detection, implement payments and ledger in Java/Spring Boot with Postgres, create Next.js admin UI, harden stack (mTLS, OIDC webhooks, encrypted secrets), run marketplace A/B tests, and implement compliance tooling.

Design, build, and maintain scalable, reliable data systems and pipelines. Partner with Product, Sales Ops, and Finance to deliver analytics and self-service tooling. Maintain SLOs, improve pipeline reliability, implement testing and documentation, and contribute to data platform strategy and operations.

Own end-to-end client data migrations: reverse-engineer legacy ETL, design and build Airflow DAGs and Spark jobs, validate and reconcile data at scale, document architecture and decisions, and coordinate cross-functional teams through go-live and hypercare.

The Senior Data Engineer will develop data engineering solutions, manage ETL workflows, and establish a new data practice while collaborating with stakeholders.

Assess datasets for ML readiness, design and iterate ML models, define evaluation metrics, perform error analysis, build reproducible workflows using AWS SageMaker, provide technical recommendations, and support implementation decisions while addressing risk and sustainment within a secure government environment.

As a Senior Data Engineer, you will design, build, and maintain scalable data platforms, ETL pipelines, and support analytics and ML workflows, ensuring data quality and cross-functional collaboration.

The Data Platform Engineer will build and maintain data pipelines, ensure compliance, develop analytics, and collaborate on a full stack product with a focus on healthcare data.

As a Senior Data Engineer, you will design and operate data transformation pipelines, workflows, and AI-assisted data visualization tools, collaborating with an experienced team.

The Cloud Data Services Engineer will support Cloud Data Services, perform database design, and implement DevOps practices in a high-performance team environment.

The Cloud Data Services Engineer will support Cloud Data Services, focusing on SQL Server and NoSQL technologies. Responsibilities include database design, performance monitoring, and automation within a DevOps environment.

The Cloud Big Data Engineer role focuses on supporting Cloud Data Services, involving database design, performance monitoring, and troubleshooting in a fast-paced environment. The role requires expertise in Microsoft SQL Server, NoSQL, and cloud application administration, while embracing DevOps practices for continuous integration and automated quality checks.

The Cloud Data Services Engineer will design and implement solutions, support production databases, plan procedures, and evaluate new cloud technologies.

The role focuses on building a Data Management Cloud Platform using Java and AWS technologies. Candidates are expected to have extensive experience in Big Data, automation, and CI/CD pipelines, along with knowledge of streaming architecture and tools like Kafka and Spark.

The Senior Big Data Developer will lead projects through the software lifecycle, including requirements capture, design, development, acceptance testing, and implementation.

The role involves Oracle database administration, data migration to cost-effective solutions, architecting solutions for legacy systems, and AWS RDS implementations.

The role involves providing application development and advisory services for various projects on a Data Lake, utilizing technologies like Hadoop and GreenPlum.

Design and develop ETL processes and data structures for banking data warehousing. Mentor junior developers and ensure solution alignment with business strategies.