Top Data Engineer Jobs in Portugal

Design, build, and maintain cloud data pipelines and data architecture on AWS/Azure/GCP. Advise clients on cloud-based ingestion and processing, collaborate with stakeholders, and deliver production-ready data products while evaluating architectural trade-offs.

Build and maintain production data pipelines and models using SQLMesh, BigQuery, and Python. Improve observability, reliability, and performance; support finance and revenue pipelines; participate in on-call rotation and own features end-to-end.

Design, build, test, and support cloud-based data engineering solutions: ETL pipelines, data workflows, APIs, and data services. Deploy and troubleshoot in Linux/cloud environments, collaborate with platform and DevSecOps teams, ensure secure coding, document data flows, and support mission-driven programs.

Build and maintain data pipelines using Python and Spark/PySpark. Work with Presto/Athena and Airflow to collect, aggregate, and store data powering BI. Emphasizes strong algorithms, data structures, and shipping high-quality software.

The Data Engineer/ETL Engineer will support cloud-based and on-prem application development, focusing on data management and analytics for defense and intelligence.

Lead architecture and delivery of frontier AI solutions: define end-to-end technical designs, establish reusable AI engineering patterns, guide platform integration and production readiness, advise cross-functional stakeholders, and ensure secure, scalable, observable AI products that are commercially viable.

As a Data Engineer, you will create and optimize datasets and data pipelines, focusing on large-scale data collection across various modalities and collaborating with multiple teams.

The AI-Native Data Engineer will build data pipelines, architect databases, design GCP infrastructure, and automate workflows for energy management using AI.

Develop and design data pipelines, optimize data delivery and automate processes to support end-to-end solutions in various settings.

As an AWS Data Engineer, you will develop data pipelines, create data models, troubleshoot issues, and collaborate with teams while utilizing tools like PySpark and SQL.

Design and own the companys end-to-end data and analytics stack: build metrics, dashboards, and reporting; instrument product and GTM signals; transform messy data into structured inputs for AI agents; and define analytics infrastructure (dbt, Snowflake, Mode) while partnering across founders, engineering, and GTM teams.

Solutions Engineers at Vori configure grocery platforms for retailers, handling data integration and customer interactions to solve complex problems.

The role involves structuring and ingesting customer data, setting up ETL pipelines, and providing solutions for data export and import.

The Principal Data Engineer will lead data architecture initiatives, design scalable data systems, and oversee data standards across teams while ensuring high-quality data infrastructure and guiding engineering teams.

The Gen AI Data Engineer will design and build distributed data systems, develop data pipelines, manage data infrastructure, and integrate technologies for real-time and batch processing, contributing to scalable analytics solutions.

Lead implementation of ETL patterns and reliable data infrastructure, partner with business and engineering teams to prioritize and deliver integrations, APIs, and reusable components, and support operational data applications in an Agile environment.

The role involves developing software solutions in collaboration with cross-functional teams, utilizing cloud technologies and agile methodologies, while optimizing processes and data analytics.

As a Business Intelligence/Data Engineer, you will analyze data structures, implement data warehousing solutions, and design data visualizations while working with AI/ML services in cloud environments.

The Data Engineer will design and implement scalable data platforms, build data pipelines, collaborate with teams to ensure data quality, and streamline processes using AWS services and big data technologies.

Leads the design, implementation, and optimization of cloud-native data infrastructure, platforms, storage solutions, and complex data pipelines. Establishes engineering standards for testing, monitoring, releases, and reliability; troubleshoots cross-system failures and leads incident reviews. Partners with infrastructure, laboratory IT, data science, bioinformatics, and scientific teams to deliver secure, scalable solutions. Mentors engineers, guides technical initiatives, and uses generative AI to accelerate development and data transformation.

Build and maintain marketing data pipelines, replace spreadsheet workflows with structured databases, automate data cleaning/deduplication and syncing, develop AI-driven reports and dashboards, and collaborate with marketing, AdOps, and engineering to ensure reliable, unified, AI-ready marketing data.

Design and implement data ingestion, transformation, and Foundry applications using Palantir Foundry AIP. Develop workflows in Workshop and Ontology Manager, integrate AI/ML models, support analytics and mission-focused solutions, collaborate with stakeholders, follow Agile and DevSecOps practices, and manage Git/CI/CD pipelines. Role requires eligibility for Secret clearance and a bachelor's degree.

Design, build, and maintain secure, scalable data pipelines and ML data workflows to support IRS fraud detection and compliance analytics. Collaborate with data scientists and stakeholders, troubleshoot production issues, produce documentation and briefings, and operate in restricted government environments.

The Senior Data Engineer will design and build data systems, mentor engineers, and collaborate with product teams to optimize data architecture and pipelines for scalability and reliability.

The Data & AI Engineer III will lead cloud data engineering solutions, develop data infrastructure, establish architectures, mentor team members, and secure data around cloud systems.