Top Data Engineer Jobs in Portugal

Design, build, and maintain scalable ETL/ELT pipelines and lakehouse data platforms on Azure and Databricks. Implement Medallion architecture and Delta Lake, enforce data governance and quality, optimize pipeline performance, and support CI/CD and environment promotion to deliver reliable financial reporting and analytics data products.

As a Data Engineer, you'll lead data engineering projects, develop data transformations, build workflows with Apache Airflow, and ensure data quality and integrity while collaborating with stakeholders.

Senior Data Engineer on PwC's Managed Data, Analytics & Insights team to design, build and manage advanced data ecosystems. Responsibilities include designing data solutions and scalable pipelines, solving complex problems, mentoring junior staff, maintaining high delivery standards, and building client relationships while aligning solutions to business context.

Design and maintain data collection infrastructure and resilient pipelines, troubleshoot and resolve data defects, implement maintenance strategies, support BI/warehousing/reporting, build reports and visualizations, and collect/extract/clean data end-to-end, including real-time streaming and performance tuning.

Design, build, monitor, and optimize large-scale cloud-native big data platforms and data lakehouse architectures. Modernize legacy Hadoop systems, migrate users to a unified platform, implement data services and ETL/transformations, improve performance and cost, and partner with business stakeholders to translate analytic needs into technical solutions.

The Data Engineer II will build and optimize data pipelines, develop reusable data sets, and ensure data integrity and security.

Build and maintain scalable, secure data pipelines and storage for multimodal clinical and NLP data; generate and process synthetic data; enable real-time model evaluation and monitoring; ensure data quality, security, compliance; create dashboards and documentation to support AI research.

As a Data Engineer, you'll transform raw data into refined offerings, collaborate with stakeholders, build central logic layers, and leverage AI tools for efficient data workflows.

As a Data Engineer at Whatnot, you'll design data architectures, implement data workflows, ensure data quality, and support analytics across teams.

Design, build, and operate scalable data pipelines and AI-ready data products from large structured and unstructured sources (OCR/images/documents). Enable production Generative AI (RAG, semantic search), ensure data quality/observability, orchestrate CI/CD and infra-as-code, and mentor engineers while collaborating with product, analytics, and compliance teams.

Design and execute data testing and validation for the National Data Warehouse. Create and run test scripts, document results, track defects, collaborate with business and technical teams, define acceptance tests, and recommend remediation. Build solutions using cloud data platforms and maintain strong IT-business relationships.

Develop, deploy, and operate production-grade Nextflow bioinformatics pipelines on cloud infrastructure. Support pipeline lifecycle, performance tuning, CI/CD and DevOps practices, and evolve an omics data platform. Collaborate with scientists and external partners, document workflows, and support users to deliver reliable omics data products for drug discovery research.

Design, build and maintain scalable data pipelines and automated workflows using Python, Airflow, DBT and cloud warehouses. Partner with Analytics, Sales and Marketing to deliver curated marketing datasets, enforce data quality through validation and CI/CD, and support production deployment and monitoring of Enterprise Data Lake/ODS solutions.

The Data Engineer will architect and develop robust data frameworks for data platforms, focusing on data transformations and automated workflows. Responsibilities include collaborating with stakeholders, ensuring data quality, and maintaining high engineering standards.

Expand and optimize data pipelines for cross-functional teams, support developers and analysts, implement process improvements, and build analytical tools for business insights.

Design and build high-volume, low-latency data solutions: ingest and normalize diverse data sources, implement ETL and streaming pipelines, build CI/CD for data software, and maintain observability and monitoring.

Develop and maintain data pipelines and BI solutions for smart factory initiatives. Design data models, document data warehouses, build KPI dashboards, support ad-hoc analysis, and collaborate with stakeholders to enable data-driven decisions.

The Associate, Data Engineer will create and optimize data pipelines, manage datasets, and collaborate with teams for data integrity and architecture improvements.

The Data Engineer will design and build data solutions, develop ELT jobs, ensure data quality, and collaborate with technical teams to align data strategies with business goals.

The Data Engineer will develop and implement ETL processes, design data architectures, work with data platforms, and ensure data solutions meet scalability and security needs. Responsibilities include mentoring junior engineers and collaborating with stakeholders to gather requirements and optimize data transformations.

Lead analytics engineering initiatives, design data pipelines, develop business intelligence solutions, and ensure data governance while collaborating with stakeholders.

Build and maintain end-to-end data and data science solutions for robotics in manufacturing. Design scalable pipelines for multimodal sensor, telemetry, image, and time-series data; enable analytics, model development, MLOps, reproducibility, and production monitoring. Partner with robotics, manufacturing, and software teams to turn raw data into curated datasets, APIs, and insights that drive operational improvements and reliability.

The Market Data Engineer will design and implement high-performance market data systems, focusing on trading infrastructure, performance optimization, and system resiliency.

The Data Engineer will build and maintain data pipelines, optimize workflows, manage infrastructure, and enhance pipeline observability while collaborating with teams for effective data delivery.

Design and operate scalable data systems for People Analytics, ensuring reliability and privacy of sensitive employee data. Collaborate with leadership to create data products for decision-making.