Top Data Engineer Jobs in Portugal

The Senior Core Data Engineer will process large data sets using Java, Hadoop, and NoSQL technologies, utilizing production-level experience for data ingestion, processing, and deployment.

Develop, maintain, and enhance software systems from requirements; review and test software components; apply software design/development methodologies; contribute to system design using COTS/GOTS; analyze system performance and processes; collaborate with users and system engineers; investigate and resolve problem areas.

The Data Engineer will manage and develop data warehousing solutions, implement ETL processes, and utilize SQL for data analysis and reporting. Experience in analytics tools and communication is essential.

Design, build, and manage batch and real-time data pipelines on GCP. Implement Terraform IAC, CI/CD, APIs, and CDC ingestion via Datastream. Build medallion architecture with Dataform/dbt, optimize BigQuery and ClickHouse models, create Airflow DAGs with monitoring, and maintain GDPR/CCPA compliance and data governance.

The Data Engineer will process raw data, develop predictive models, and conduct statistical analysis to support business decisions, collaborating with engineering teams and business partners.

The Data Engineer will gather and process large datasets, develop algorithms, conduct data analysis, and improve predictive models for business decisions.

The Data Engineer will gather and process data, analyze trends, support business decisions, and collaborate on predictive models while improving algorithms and efficiency.

Build, maintain, and optimize ETL/ELT data pipelines using Databricks, Apache Spark, and SQL. Support data ingestion, transformation, SSIS integration, and SQL Server development. Troubleshoot data quality, assist production support, document processes, and collaborate with analysts and stakeholders. Support data governance, HIPAA compliance, and healthcare data initiatives.

Design and develop scalable backend services and data ingestion solutions, collaborating in an Agile environment to optimize speed and scalability.

The role involves designing and scaling data infrastructures for private equity, developing ETL/ELT pipelines, ensuring data quality, and collaborating with various teams on data governance.

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 role involves designing and developing data applications, working with large data sets, and requires expertise with various data processing technologies. Candidates should have strong analytical skills and experience in prototyping software applications.

The Azure Data Engineer will design and maintain data pipelines using Azure technologies, optimize data flows, and ensure data quality, collaborating with various stakeholders.

The Data Engineer will develop secure, scalable data pipelines for IRS applications, supporting complex analytics and machine learning to combat fraud and ensure compliance. Responsibilities include pipeline engineering, troubleshooting, and collaboration with data teams to create production-ready analytics solutions.

Design, build, and maintain data pipelines and RESTful APIs for incident response tooling. Develop ETL/data flows, spot data anomalies, optimize pipeline performance, collaborate on CI/CD and code reviews, and work with containerized and cloud-native data services.

The Cloud Data Engineer will design and develop data warehouse solutions, create efficient data pipelines, collaborate with teams, and monitor system health.

As a Data Engineer, you will develop data pipelines and APIs, configure cloud resources in AWS, and translate business needs into technical specifications.

Looking for a Data Engineer experienced in Dataiku to design and maintain data pipelines and infrastructure, ensuring data flow and integration across teams.

The DMS Data Engineer is responsible for analyzing raw data, building data systems and pipelines, conducting complex data analyses, and collaborating on projects to enhance data quality and reliability.

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.

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.

Designs, builds, and maintains scalable batch and streaming data pipelines, ETL/ELT workflows, data models, and Python transformations. Writes optimized SQL, monitors pipeline reliability, troubleshoots failures, implements data-quality validation, and supports security and governance practices. Collaborates with engineers, analysts, stakeholders, and clients to define data contracts, improve platforms, document lineage, and deliver reliable analytics data.

Administer, maintain, and optimize SQL and NoSQL database environments; apply data warehousing concepts; perform data management and maintenance using SQL, Python, and Apache Spark; support cloud database infrastructure with Git, AWS, or Azure; and provide database support for Tableau and Power BI reporting.

Administer, maintain, and optimize SQL and NoSQL database environments. Apply data warehousing and data management practices, using SQL, Python, and Apache Spark. Support database infrastructure with Git and AWS or Azure, and provide database support for Tableau and Power BI reporting and visualization tools.