Top Data Engineer Jobs in Portugal

Data Engineers at CapTech build and maintain data pipelines on cloud platforms, advise clients on technology usage, and ensure data architecture maximizes client value.

Data Engineer to develop data pipelines using AWS, Azure, or GCP, advise clients on cloud resources, and collaborate with stakeholders to enhance data architecture.

The Data Engineer will develop data pipelines, advise clients on cloud solutions, and collaborate to maximize data architecture value.

CapTech seeks a Data Engineer to develop data pipelines, advise clients on cloud technologies, and collaborate on data architecture solutions while leveraging AWS, Azure, or GCP.

The Senior Data Engineer will design and maintain scalable data pipelines and ETL processes using Databricks, integrate DevOps tools, and ensure data modeling adheres to best practices.

The Data Engineer will develop and maintain ETL processes using Python and Azure Synapse, ensuring data quality, performance optimization, and documentation.

Design, build, and operate scalable data pipelines and platforms for enterprise clients. Develop ETL/ELT workflows, data ingestion and processing for structured and unstructured data, guide cross-functional teams, and support monitoring, scaling, and operationalization of data solutions.

Design, build, test, and operationalize data pipelines and solutions. Analyze data sources, apply transformations and quality controls, resolve incidents, and collaborate with teams to deliver data products supporting analytics, BI, and AI/ML use cases.

Design, build, and maintain data pipelines and platforms to ingest, prepare, and organize structured and unstructured data. Develop ETL using Java/Python/SQL/Scala, work with PostgreSQL or Kafka, and leverage AWS services. Collaborate with cross-functional teams in an agile environment and support real-time/streaming applications while meeting security and clearance requirements.

The ETL Software Engineer will develop and manage ETL pipelines, work with relational databases and SQL, automate tasks, and ensure data quality. The role requires TS/SCI clearance and offers opportunities to work on mission-driven projects.

Design, build, and maintain cloud-native AWS data platforms and scalable data lake/warehouse solutions. Develop and deploy data pipelines for structured and unstructured data to support AI/ML and BI, lead cross-functional teams, and manage cloud migration and modernization efforts. TS/SCI with polygraph and a CS bachelors degree required.

The Technical Lead oversees data engineering teams, mentors engineers, and contributes hands-on to design, development, and delivery of data solutions in AWS using Databricks.

As a Senior Azure Data Engineer, you will design and build data pipelines, implement data models, and lead migrations to Azure, while ensuring optimal performance and governance.

Design, build, and maintain Finance data models and scalable data pipelines on GCP. Automate workflows (Python, Airflow/Astronomer, Jenkins), ensure data governance and lineage, collaborate with stakeholders, conduct code reviews and testing, and evaluate new data sources and technologies to support financial insights.

Design and maintain data pipelines and lake platforms, optimize data processing with cloud technologies and collaborate with team members for AI initiatives.

The Data Engineer will build the data infrastructure, including ingestion pipelines and backend services, while ensuring data accessibility and quality for the company.

The Data Engineer Consultant will develop scalable data infrastructure, optimize SQL queries, design dimensional models, create visual dashboards, and collaborate with clients to meet data needs.

The Data Engineer will clean, manage, and analyze datasets, automate ETL processes, and collaborate with traders and software engineers to derive insights.

Support manufacturing operations by configuring and maintaining MES and SAP, developing manufacturing methods and processes, enabling new-product setups and pilot builds, conducting UAT, troubleshooting system issues, extracting and translating data for engineering/business teams, and representing manufacturing on cross-functional projects to drive process improvements.

The Data Engineer will design and develop data pipelines for quality monitoring, assess data integrity, and build web applications supporting user validation and analysis.

Build and maintain ETL/ELT pipelines in a lakehouse/cloud environment, ensure data quality and lineage, and apply classical statistics and ML (anomaly detection, regression, time-series) to support operational decision-making and stakeholder reporting.

Design, implement, and test a custom web application for the companys cloud data lake. Build scalable, resilient features, ensure data accuracy, integrity, and security, troubleshoot defects, participate in design/code reviews, mentor engineers, and join on-call rotations to support critical systems.

The Junior Data Engineer will work with data to enhance trading systems, support data warehouses, and collaborate on technical solutions with the team.

Design, build, and maintain scalable ETL/ELT pipelines using Python/PySpark and Snowflake. Implement Snowflake objects and optimize performance, ingest structured and semi-structured data, apply dimensional modeling, enforce data quality and governance, monitor pipelines, and collaborate with architects and stakeholders to deliver cloud-based data platform solutions (Azure).

Design, implement, and optimize large-scale data processing on Databricks and Spark. Build ETL pipelines, integrate data across AWS services (Redshift, RDS), orchestrate workflows with Airflow, and ensure data warehousing and engineering best practices. Lead and mentor development teams and collaborate with cross-functional stakeholders to drive data strategy and execution.