Top Data Engineer Jobs in Portugal

Design and deliver scalable Databricks/Spark/Delta Lake data pipelines, implement GitLab CI/CD and IaC/container workflows, apply SOLID engineering and testing frameworks, mentor peers, integrate AI-driven monitoring, and collaborate with Data Science and Product to productionize ML solutions on AWS while ensuring security and reliability.

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.

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.

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.

Lead design, development, and operation of large-scale Spark-based data pipelines and lakehouse solutions. Write and review Python/PySpark and Spark SQL production code, optimize Spark workloads on EMR/Databricks, manage Apache Iceberg table operations, drive AI-assisted engineering adoption, automate reliability and CI/CD practices, and lead technical evaluations and communities of practice.

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.

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.

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 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.

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.

Lead design, develop, and maintain secure, scalable data and AI-driven systems. Build data pipelines on AWS/Databricks, write production code, drive AI-assisted engineering adoption, enforce validation/security standards, and mentor teams on responsible AI practices.

Lead engineering and deliver secure, scalable data and LLM-based systems for a Global KYC and Risk Assessment Data Platform. Define architecture, engineering standards, AI/LLM governance, and drive adoption of AI-assisted development practices while mentoring teams and ensuring operational stability and observability.

Design and deliver enterprise-scale data models and analytics-ready datasets in Snowflake; build reliable ELT/ETL pipelines (batch and near-real-time); enforce data quality, observability, and secure handling of PII; optimize performance and publish curated data to downstream systems while collaborating with product, operations, and engineering teams.

Design and build data infrastructure, pipelines, and transformations using Azure Data Factory, Azure Databricks, and Snowflake. Develop data architecture and modeling, maintain data lakes/warehouses, ensure data quality and security, optimize performance, and collaborate with clients to deliver tailored data solutions and governance.

Lead design and implementation of scalable data infrastructure, pipelines, and transformations using cloud platforms. Build and optimize data warehouses (Snowflake, Databricks), orchestrate workflows (Airflow, Hadoop), ensure data quality and security, and coach teams to deliver analytics solutions that drive tax practice insights and client outcomes.

Lead design and implementation of data infrastructure, pipelines, and warehouses using Azure Data Factory, Databricks, and Snowflake. Manage data modeling, quality, security, and analytics frameworks. Lead client accounts, mentor teams, and drive innovation to deliver data-driven business insights.

Lead design and delivery of agentic data and AI platforms for vehicle product engineering. Build large-scale batch and streaming pipelines, semantic models, observability, and agentic workflows that detect anomalies, recommend or enact remediations, and support production-grade ML services. Drive architecture, governance, standards, mentorship, and cross-functional execution to scale secure, resilient, and observable systems across global vehicle design and manufacturing.

Design, build, and operate production AI and data systems for marketing: LLM/agent orchestration, retrieval pipelines, data pipelines, CDP and warehouse architecture, automation of manual workflows, data quality and reliability, stakeholder collaboration, and mentoring. Ship production-grade Python and SQL solutions and evaluate/monitor AI systems.

Design, build, and support complex batch and streaming data pipelines from structured and unstructured sources. Collaborate with engineering and analytics to deliver accurate, performant data, automate processes, maintain dev/test/prod environments, and participate in on-call rotation.

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.

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.

Build, test, monitor, validate, and support scalable ETL/ELT data pipelines and validation frameworks in Azure/Databricks. Perform source-to-target validation, data profiling, reconciliation, anomaly detection, automation, and production support to ensure data quality and reliability for analytics and reporting.

The Principal Data Engineer will lead data engineering efforts on public cloud, design scalable solutions, build data pipelines, and drive deliverables with a high level of technical expertise in relevant technologies.

The Solutions Data Engineer will manage data integrations end-to-end, utilizing FloQast's Data Platform and Data Studio to connect source systems and transform data for reliable outputs across applications.

Leads software engineering efforts for a data platform within an agile corporate technology team. Designs, develops, tests, debugs, and maintains secure, scalable production systems; reviews code; improves operational stability through automation; and promotes responsible AI-assisted development practices. Evaluates vendors and architectural solutions, coaches engineers on secure AI use, and applies cloud-native technologies, software development lifecycle practices, resiliency, and security standards in financial services systems.