Top Data Engineer Jobs in Portugal

Design, build, test, and maintain secure, scalable data collection, storage, access, and analytics solutions. Develop and maintain ETL pipelines and data architectures, update logical/physical data models, review data controls, perform statistical data analysis, customize tooling to generate products, and work with SQL and NoSQL databases.

Build, model, and maintain scalable BigQuery-based data solutions on GCP. Implement performant data models, storage partitioning/clustering, ETL improvements, data validation, and documentation. Collaborate with architects, data scientists, and engineers to deliver governed, high-quality data for reporting and AI initiatives.

Design, build, and maintain scalable Snowflake-based data platforms and ETL/ELT pipelines; operationalize AI/ML models; automate processes; monitor and optimize code and data systems; support data governance and engage cross-functionally to deliver analytics and predictive solutions.

Design, build, and maintain scalable ETL/ELT pipelines and data warehouse architecture. Partner with cross-functional teams to define KPIs, ensure data quality and governance, own billing data infrastructure, and deliver dashboards and analytics for leadership while mentoring peers.

Design, build, and optimize data pipelines and architecture; extend ML platform; implement ETL using SQL, Python, and AWS; build analytics tools; supervise and mentor junior data engineers; collaborate with development and analytics teams to support data-driven products.

Design, build, and own scalable data pipelines and evaluation systems that power production AI features and internal analytics. Ensure data quality across ingestion, modeling, and reporting, collaborate with ML and analytics teams, deploy and monitor ML systems, and establish standards for data work and evaluation.

Design, build, and maintain production-grade ETL/ELT pipelines and analytics-ready data products on Databricks and cloud platforms. Collaborate with data modelers, governance, and cross-functional teams to implement dimensional models, optimize pipeline performance, ensure data quality and support BI consumption, while following Agile/SAFe practices.

Support development, testing, and maintenance of ETL/ELT pipelines on Databricks and Azure. Ingest, transform, validate data, assist with dimensional modeling, monitoring, troubleshooting, and documentation. Participate in code reviews, deployments, Agile ceremonies, and collaborate with business and technology partners to prepare data for analytics and reporting.

Lead design and modernization of scalable, secure data systems and real-time pipelines for xOT cybersecurity. Create data contracts, observability, lineage, and cross-functional solutions supporting cloud and on-prem deployments, Kubernetes, and stream processing to enable threat detection and intelligence.

Design, build, and operate scalable data platforms and ETL/ELT pipelines using Python, SQL, Airflow, and AWS. Optimize data warehouses, ensure data quality and governance, implement CI/CD and infrastructure-as-code, and collaborate with cross-functional teams while mentoring engineers.

The Data Engineer will design and build scalable data systems, contribute to the architecture of the data platform, and collaborate with AI/ML engineers to enhance automation and intelligence in Canoe's systems.

The Data Engineer III will design, implement, and optimize data services, ensuring they meet business needs and drive automation and best practices across Crunchyroll's data environments.

Develop, curate, and publish authoritative geospatial data products in ArcGIS Portal; build Python data-processing pipelines; and create Tableau dashboards and web maps. Manage metadata, hosted feature layers, and data discoverability while partnering with mission users to transform large spatial and tabular datasets into operational visualizations and automated workflows.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

Design, build, and maintain data architectures and pipelines to ensure data quality, lineage, and accessibility. Implement ingestion frameworks and transformations across cloud and on-prem platforms, enable data consumption (APIs, views, extracts), monitor data observability, and collaborate cross-functionally to meet privacy and business requirements. Work may include nights/weekends and requires independent technical judgment.

Join BlackRock's Advanced Data Analytics team to deliver research and data solutions for structured products, leveraging data technologies and statistical methodologies.

As a Senior Associate in Data Engineering at PwC, you will design and implement data architecture strategies, analyze complex issues, mentor junior members, and build client relationships while ensuring adherence to project standards.

As a Senior Manager in Data Engineering, you will lead teams to design data architectures, develop data solutions, manage client engagements, and ensure compliance with data governance policies.

Lead data engineering projects, develop and implement data pipelines and architecture strategies, manage data quality, and mentor team members at PwC.

As a Manager in Managed Services, you'll lead data ecosystems projects, mentor juniors, manage client accounts, and deliver data strategies to optimize operations and drive insights for clients.

Design, build, and maintain scalable data pipelines and API integrations; implement data quality monitoring and alerting; troubleshoot data issues; collaborate with business stakeholders; support CI/CD processes and scale architecture for future needs.

The Principal Data Engineer at NBCUniversal leads the development of data applications, manages data pipelines, and collaborates with teams while coaching junior engineers. Responsibilities include designing scalable data solutions and integrating AI technologies.

Design, build, and optimize scalable Azure data pipelines and AI platforms using Databricks, Spark, and Python. Operationalize ML models, maintain feature stores and real-time streaming, ensure data quality/governance/security, implement CI/CD, provide production support, and develop reusable frameworks and responsible AI-powered solutions.

Build scalable Databricks/Spark data pipelines, implement automated GitLab CI/CD workflows, apply SOLID engineering and testing to ensure pipeline reliability, integrate AI/ML and NLP tools, mentor peers, and operationalize models in AWS production environments.

As a Senior AI/Data Engineer, you will design and maintain scalable data and AI infrastructures, partnering with cross-functional teams to deliver reliable data systems and support AI-driven business capabilities.