Top Data Engineer Jobs in Portugal

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

Lead cross-functional Agile teams to design, build, test, and support cloud-based data solutions. Develop full-stack data engineering systems using Java/Scala/Python, RDBMS and NoSQL, Redshift/Snowflake, and distributed tools (Hadoop, Spark, Kafka). Mentor engineers, perform code reviews and unit testing, and collaborate with product managers to deliver scalable, performant data products.

The Senior Lead Data Engineer designs and develops technical solutions, leads a team of developers, and utilizes big data and cloud technologies to deliver robust solutions for Capital One.

Lead Data Engineer responsible for designing, developing, and supporting technical solutions in a fast-paced environment while collaborating with Agile teams and utilizing emerging technologies.

Lead and mentor data engineering teams to design, build, test, and support cloud-based, full-stack data solutions. Work with big data, streaming, and data warehousing technologies (Redshift/Snowflake), collaborate with product managers, and ensure high-quality, performant code and systems.

Lead a team of engineers to design and implement data solutions using cloud technologies, optimizing data pipelines and collaborating with Agile teams to deliver impactful data-driven products.

The Lead Data Engineer will design, develop, and support technical solutions, utilizing big data technologies and cloud platforms, while collaborating with Agile teams.

As a Lead Data Engineer, you will develop cloud-based data solutions, collaborate with teams, and stay updated on technology trends to drive data transformation.

Lead Data Engineer designs, develops, tests, and supports cloud-based data solutions. Collaborates with Agile teams, mentors engineers, implements big data and streaming systems, and optimizes code for performance to deliver data-driven products.

Own and build Grow Therapy's data security infrastructure: automated data classification, field-level masking/tokenization, encryption and key management, secure data connectors to AI tooling, and access controls. Define a multi-year vision, implement pipelines and services, and partner across Data, Engineering, and Detection & Response to make secure-by-default the company standard.

Lead design and delivery of Klaviyo's scalable data platform (streaming, batch, lakehouse, governance). Define SLOs, author ADRs/RFCs, implement ingestion/CDC, processing, storage, catalog/lineage and access controls. Optimize performance/cost, apply ML/GenAI to data workflows, partner with product/analytics, contribute code/reviews, and mentor senior engineers to enable reliable, multi‑tenant data at scale.

Lead the development of healthcare applications and data systems, focusing on audience intelligence and compliance. Design scalable data pipelines, APIs, and reporting systems while ensuring high data quality and security in regulated environments.

The Lead Software Engineer will build healthcare applications and data systems focusing on audience intelligence, while leading development of scalable infrastructure and ensuring compliance with privacy regulations.

As a Senior Developer Advocate, you will lead community engagement in Data Observability, create content, mentor teams, and enhance product feedback from engineers.

Lead discrete-event simulation modeling of vehicle production systems using C-Draw2 and Siemens Plant Simulation to identify bottlenecks and optimize throughput. Manage model conversion, develop custom library objects and reports, validate performance datasets, mentor a team of simulation engineers, and collaborate with manufacturing stakeholders to implement cost-effective automation and material flow improvements. Support digital twin initiatives and provide leadership-level reporting to Manufacturing Leadership.

Lead Data Engineer responsible for designing, developing, testing, and supporting cloud-based data publication and transformation solutions. Collaborate across Agile teams to build distributed, real-time data pipelines and data warehousing (Redshift/Snowflake), perform unit tests and code reviews, mentor engineers, and adopt emerging technologies to deliver scalable data platforms.

Design, build, and maintain scalable Spark/Python data pipelines and automated workflows. Enforce data governance, quality, lineage, and observability. Support ML pipelines (feature engineering, validation, monitoring) and document data assets, contracts, and standards.

The Lead Data Engineer will design, implement, and maintain data pipelines for mission-relevant data, ensuring compliance with security frameworks and optimizing data accessibility and interoperability across mission systems.

Operate and evolve AMP platform to ensure reliability, security, compliance, cost efficiency, and operational excellence. Monitor health and capacity, manage incidents and escalations, provision Azure/Fabric resources, enable onboarding, drive security and compliance remediation, optimize costs and capacity, coordinate with product groups and vendors, and improve automation, observability, and operational tooling.

Lead architecture and delivery of scalable, secure enterprise data and AI integration solutions. Own integration strategy, API‑first and cloud‑native designs, data product onboarding, governance, observability, and migration to Azure/Databricks/Microsoft Fabric while guiding cross-functional teams and ensuring compliance, performance, and operational readiness.

Develop, optimize, and support ETL/data integration solutions (SSIS) to automate data delivery. Collaborate with analysts, senior developers, and architects; monitor executions, troubleshoot data issues, and follow established SDLC practices. Hybrid work with periodic on-site presence.

Design, build, and maintain scalable ETL pipelines and a cloud-based data platform. Create dashboards, troubleshoot data discrepancies, implement testing/CI/CD/IaC improvements, and collaborate with stakeholders, software engineers, and data scientists to deliver reliable BI solutions.

Build and maintain scalable data pipelines, warehousing, and analytics tooling to support AI safety monitoring, abuse detection, and enforcement. Integrate multiple data sources, implement data quality and governance, create dashboards and self-service tools, and partner with research and policy teams to inform safety interventions.

Design, build, and own scalable ETL pipelines, dashboards, and data quality processes. Troubleshoot discrepancies, expand the cloud data platform, implement CI/CD and IaC practices, and collaborate with stakeholders, developers, and data scientists to deliver BI solutions.

Lead design and implementation of scalable cloud data lakes, warehouses, and marts. Build ELT/ETL pipelines, apply Data Vault 2.0 and dimensional modeling, implement data quality, lineage, observability, and governance. Optimize Snowflake/Databricks/Synapse platforms, champion CI/CD and DataOps, mentor engineers, and enable AI/ML-ready data products through collaboration with architecture and product teams.