Top Data Engineer Jobs in Portugal

Design, evolve, and maintain large-scale ETL/ELT pipelines, data warehousing, and monitoring. Collaborate with internal stakeholders, implement CI/CD and Airflow orchestration, ensure security/RBAC and scalability, and improve BI dashboards and data governance.

The Staff Engineer will design and maintain data products, lead projects, mentor engineers, and optimize data pipelines while collaborating across teams using Agile practices.

Design and operate petabyte-scale end-to-end data pipelines for autonomous driving: onboard upload, cloud preprocessing, dataset production, and model training input. Build data cleaning, annotation QA, lineage, versioning, metadata management, and high-throughput distributed processing. Optimize I/O, memory, transmission, and containerized deployments; support cross-team collaboration and algorithm iteration.

The Sr. Data Engineer will build and manage data pipelines for large datasets, collaborate with teams, and leverage cloud technologies for data processing.

Lead Data Engineer responsible for defining architecture, engineering standards, and best practices for the enterprise data platform, collaborating with distributed teams for modernization and scalability.

Design, implement, and maintain scalable Data Lake architectures; integrate Data Lake with Stardog knowledge graph; optimize ETL/ELT and Delta Lake pipelines; enforce DoD IL-4/IL-5 security, IAM/RBAC, and Unity Catalog governance; produce compliance and performance reports; support DevSecOps, CI/CD, and cloud integrations across AWS/Azure/GCP.

Build, enhance, and sustain Army applications integrating AI-enabled analytics and Vantage; perform data mining, preprocessing, and modeling; develop and maintain Microsoft 365 SharePoint sites, manage permissions across SharePoint/Qlik/Power Apps, refine data governance artifacts, and support verification, validation, and user issue resolution.

Design, build, and operate scalable ingestion, curation, and metadata-enrichment pipelines for enterprise data catalog and discovery. Ensure data quality, schema evolution, lineage, and cost-efficient large-scale processing; translate technical concepts for non-technical stakeholders and support downstream mission use.

Build and own customer-facing data products and services: in-dashboard SQL, bulk exports, AI-powered analytics, backend services/APIs and query layers over large datasets. Partner with product and design, mentor engineers, and shape technical direction and strategy.

Design, build, and operate Persona's large-scale data platform: datalake and lakehouse, streaming and batch ingestion (including CDC), high-throughput data-movement services, real-time serving layer, and query/analytics capabilities. Drive architecture decisions, performance, reliability, and cost, and lead multi-quarter infrastructure projects while mentoring engineers and partnering with infrastructure, data science, and product teams.

Build customer-facing data products and backend services powering query, export, and AI-driven analytics over large, real-time datasets. Collaborate with product, design, data science, and engineering to deliver performant, secure, data-intensive features and APIs.

As a Software Engineer on the Data Infrastructure team, you will design, build, and maintain data platforms, implementing data models and ETL pipelines while collaborating cross-functionally.

The Senior Data Engineer will design, implement, and maintain data pipelines, improve data quality, and support investment data management, collaborating within a team to enhance decision-making and reporting capabilities.

Support government analytics for integrated combat and weapons systems using MATLAB or Python. Analyze test data, develop automation scripts, produce technical reports and visualizations, collaborate with multidisciplinary teams, and improve data analysis workflows under government direction.

Lead design, build, and productionize scalable ML systems on cloud platforms. Provide technical leadership, mentor teams, translate business needs into data-driven solutions, work with large datasets, implement recommender/NLP/vision models, leverage LLMs and agentic architectures, and support business development and client engagements.

Design, develop, and productionize scalable machine learning and data science solutions for clients. Analyze very large datasets across cloud platforms, implement recommender/NLP/computer vision and LLM-based systems, optimize for performance and scalability, leverage containerization and data warehousing, and lead/mentor junior practitioners while supporting business development and client strategy.

Lead design and delivery of end-to-end, production-scale ML systems on cloud platforms. Provide technical leadership, mentor teams, analyze and transform large datasets, implement recommender/NLP/risk models, productionize scalable ML, and grow practice through client-facing activities and business development.

Design, build, and productionize scalable machine learning systems; analyze and transform large datasets; implement recommender, NLP, and other analytic solutions; deploy models in cloud/enterprise environments; collaborate with clients and lead junior team members while contributing to business development.

Design and maintain a dbt-based business data layer for GTM metrics, centralize and reconcile multi-source data, implement automated data quality and reconciliation checks, align and document metrics with stakeholders, mentor analytics team, and lead root-cause investigations into complex data anomalies.

Lead and mentor a distributed data engineering team while architecting and building a next-generation, largely open-source data platform. Own hands-on POCs, pipeline design, schema and query optimization, ETL reliability, observability, testing, and CI/CD. Evaluate and recommend technologies, drive migration from vendor lock-in, and translate advertising and market research needs into robust technical solutions.

Design, implement, and maintain cloud-based data pipelines and architectures (ETL, data lake/warehouse). Advise clients on best practices, collaborate with product owners, mentor engineers, and deliver scalable distributed data solutions using cloud platforms and orchestration tools.

Design, implement, and maintain cloud-based data pipelines and architectures across AWS/Azure/GCP. Advise clients on best practices, partner with stakeholders to translate requirements, provide technical leadership, and mentor engineers while leveraging ETL/orchestration tools, data warehouses/lakes, databases, and programming languages for scalable data solutions.

Design, develop, and maintain batch and streaming data pipelines and ETL for large unstructured datasets. Build and operate CI/CD pipelines, containerize applications with Docker, deploy on Kubernetes, and collaborate with developers, data scientists, SMEs, and cyber analysts to deliver data management solutions.

Lead design and build of Snowflake-native medallion data architecture, ETL/ELT pipelines, master data and governance, and an enterprise semantic layer. Partner with Finance to produce reliable financial data products, optimize performance/cost, enforce data quality and compliance, mentor junior engineers, and support AI use cases and observability.

Design and build scalable Microsoft Fabric pipelines and lakehouse models, optimize Power BI semantic models and refresh strategies, enforce SDLC and CI/CD best practices, mentor teammates, and ensure SLA-driven, client-facing analytics reliability and performance.