Top Data Engineer Jobs in Portugal

Develop core data management and access frameworks for relational and graph information models in ArcGIS Enterprise. Integrate with relational and NoSQL databases, build full-stack components, collaborate in an Agile Scrum team, and research/extend DBMS support.

Partner with portfolio-company leaders to translate business problems into quantitative frameworks, build predictive models and analyses, and drive strategy and execution. Lead AI assessments, identify growth opportunities, present recommendations to executives, and implement measurable data-driven initiatives across finance, pricing, operations, and marketing.

Design, build, and maintain data pipelines and models for hardware manufacturing, device traceability, yield, and supply chain. Integrate MES/ERP/IoT data into a lakehouse, ensure end-to-end data quality, security, and governance, and partner with Hardware, Operations, and Quality teams. Support lakehouse architecture (Iceberg, Databricks, dbt) and reduce single-point-of-failure risk for manufacturing data.

The Senior Data Engineer will build data pipelines and infrastructure, modernize legacy systems, and ensure data reliability for analytics at ABCorp.

Design and implement scalable enterprise data and lakehouse architectures; build and optimize cloud-based ETL/ELT and streaming pipelines for high-volume telematics/IoT data; integrate enterprise systems (ERP, CRM, service/warranty); prepare and enrich data for analytics, predictive maintenance, and AI/RAG applications; collaborate on governance, security, observability, and DataOps practices.

Apply mathematical modeling, statistical analysis, and systems optimization to evaluate and improve NexusOne platform performance. Define and validate data requirements, analyze pipeline throughput and governance compliance, and present findings to stakeholders. Collaborate with engineering and delivery teams to modernize legacy systems (Spark/Airflow), enable AI pipelines, and recommend NexusOne configurations to meet performance, compliance, and AI readiness goals.

Own and build Tern's AI and data systems end-to-end: data pipelines, production AI services, evaluation harnesses, monitoring and reporting. Ensure data quality across ingestion, modeling, and reporting, ship reliable production software, and collaborate with product squads to deliver trustworthy AI features and advisor-facing analytics.

Develop, integrate, deploy, and sustain satellite ground software including full‑stack development, high‑throughput telemetry pipelines, data cleaning and storage design, dashboards, CI-integrated quality checks, operations support, test automation, and launch event support. Work is 100% onsite in McLean, VA and requires active Top Secret clearance.

Lead design and delivery of AI-powered, data-driven workflows and foundations: build retrieval/evidence pipelines, durable job execution, monitoring/evaluation, data contracts, identity resolution, and reusable abstractions while partnering with product and engineering to measure adoption and impact.

Own and evolve the data platform by leading architectural evolution, collaborating with teams for strategic data initiatives, and ensuring reliable data systems.

The Sr .Net Developer will enhance and maintain the ADE SIS web applications, mentor staff, and ensure accurate data submission and analysis.

Supporting Regulatory Reporting in the capital markets sector, focusing on Axiom SL implementation and integration with Hadoop as a data repository.

The GTM Engineer leads the design of a data layer and autonomous systems for AI-driven revenue optimization, collaborating with leadership on growth strategies.

The Senior Data Engineer will lead MLOps efforts to streamline model delivery and data processing, implementing automation throughout the machine learning lifecycle and enhancing collaboration between data scientists and engineers.

Design, build, and scale streaming and batch data pipelines, embedding workflows, and vector store integrations to support AI applications. Implement AI-optimized data models, ensure observability and data quality, and collaborate across infra, ML, and product teams while mentoring engineers and delivering production-ready, reliable data foundations.

Founding member of a data engineering team building a Databricks-first, multi-tenant lakehouse. Design and implement batch ingestion, tenant-isolated data models, provenance-aware pipelines, nightly profile enrichment, dbt transformations, orchestration, and AI enablement for agents, RAG search, APIs, and exports.

Develop and maintain thermofluid, lumped-parameter models and simulation tools for the Raptor engine; perform engine cycle analysis and anomaly resolution; build data pipelines, automation, and web tools to translate test data into flight predictions; collaborate across teams to improve interoperability, vehicle-integrated models, and software used for GNC and flight performance prediction.

Develop, maintain, and improve lumped-parameter thermofluid models and simulation tools for the Raptor engine; perform engine cycle analysis, anomaly resolution, data-driven root cause analysis, and generate automated predictions for test and flight performance. Build tooling, data pipelines, and integrations to support GNC, flight software validation, and cross-team interoperability.

Develop and maintain core data management frameworks for ArcGIS, collaborating on innovative projects and contributing to relational and NoSQL database integration.

Design and develop scalable offline indexing pipelines for Slack's search infrastructure, ensure system reliability, and optimize search performance while collaborating with multiple engineering teams.

Hands-on Senior Data Engineer to maintain and optimize an Oracle-centric enterprise data warehouse, manage cloud-to-Oracle integrations, evolve ETL/ELT pipelines, and help build a hybrid lakehouse (Apache Iceberg, OCI Object Storage, Parquet). Requires performance tuning, Linux administration, Java debugging, and close collaboration with senior client stakeholders. Contractor role with possible conversion to full-time.

Design, build, and maintain scalable data pipelines and backend systems to collect, process, and store aircraft telemetry and logs. Integrate diverse data sources, optimize batch and interactive services, and monitor pipeline performance and data integrity to support analysis, ML model training, and flight operations.

Design, build, and operate distributed, data-intensive backend systems and pipelines. Own production data infrastructure (streaming, batch, analytical stores), debug production incidents, participate in on-call rotations, partner with product and frontend teams, write/review architecture and code, and improve observability, reliability, and deployment practices.

This role involves leading data infrastructure modernization efforts, architecture reviews, and migration planning while providing technical mentorship and establishing operational standards.

Lead design, integration, testing, and deployment of tactical data link and communications capabilities (Link 22/Link 16). Develop software requirements, MBSE artifacts, and interoperability/interface definitions. Support developmental and operational test/evaluation, acquisition documentation, and advise program leadership on performance, schedule, and cost. Interface with DoD, USAF, Army, and joint stakeholders.