Top Data Engineer Jobs in Portugal

Own and modernize core data infrastructure and pipelines to ensure accurate usage capture, transformation, and monetization. Contribute to architecture, maintain integrations with billing/CRM/payment platforms, evolve customer account UIs, and improve legacy Laravel systems while collaborating across a distributed team.

Build and operate LLM-augmented ETL pipelines and domain-specific information retrieval systems. Design, deploy, and optimize production-grade data ingestion, databases, and infrastructure on AWS. Own projects end-to-end, collaborate with leadership and customers, and refine data priorities based on user feedback.

Lead engineering strategy and hands-on implementation for Finance & Actuarial data platforms. Architect no-touch automated data pipelines, drive cloud migrations (Azure Synapse/Databricks/Snowflake), embed AI-assisted development and modern DevOps, establish CI/CD and runbooks, resolve complex incidents, evaluate tooling, and mentor engineering squads while communicating strategy to executive stakeholders.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.

Lead architecture and strategic direction for Pinterest's data warehouse, analytics tools, and data governance. Drive cross-functional initiatives to build scalable data platforms, AI-assisted pipeline tooling, and analytics capabilities. Mentor engineers, define policies and tooling, and deliver measurable adoption and business impact across the company.

Design and implement scalable AWS-based data infrastructure using Spark and Scala. Build fault-tolerant batch and streaming pipelines, optimize storage formats and engines, collaborate with Data Science and Product, implement automated data quality checks, and deliver performant data assets and APIs.

Design and implement scalable data infrastructure in AWS using Spark and Scala. Evolve core data pipelines, store data in optimal engines/formats, build knowledge graphs and APIs, optimize AWS resources, implement automated data quality checks, and collaborate with Data Science and Product teams to deliver reliable, large-scale data services.

Lead design and operation of identity resolution and data governance systems. Build batch and streaming pipelines, APIs, and tooling for identity ingestion, matching, lineage, quality, access controls, and privacy compliance (GDPR/CCPA). Collaborate with product, analytics, legal, and security to ensure privacy-by-design, monitoring, and documented runbooks.

Lead design and implementation of Pinterest's exabyte-scale data lake storage and metadata systems. Drive architecture and execution for scalable storage features supporting large ML/AI workloads, collaborate across data/ML/infrastructure teams, and contribute to open-source projects (Iceberg, Spark, Flink).

Lead design and implementation of identity resolution and data governance systems. Build batch and streaming pipelines, APIs, and services to ingest, normalize, link, and version identity data. Ensure auditable matching, data lineage, quality checks, schema enforcement, access controls, and privacy-by-design. Collaborate cross-functionally with product, analytics, legal, privacy, and security teams and create documentation, monitoring, and runbooks.

Design and implement scalable data infrastructure and pipelines on AWS using Spark and Scala. Build fault-tolerant batch and streaming workflows, optimize storage formats and engines, enforce automated data quality checks, and collaborate with Data Science and Product teams to deliver reliable data assets and APIs.

Design, build, and optimize scalable data infrastructure and pipelines on AWS using Spark/Scala. Store and model data in appropriate engines and formats, implement knowledge graphs accessible via batch jobs and APIs, enforce automated data quality checks, and collaborate with Data Science and Product teams to deliver performant, cost-effective data services.

Lead development of large-scale data analysis and validation workflows for autonomous driving ML. Design metrics, build datasets, run statistical error and regression analyses, collaborate with ML and software teams, and maintain AWS/Kubernetes orchestration for large-scale evaluation.

Design and own end-to-end data quality systems for managed AI data studies: define rubrics, sampling plans, automated checks, launch gates, drift detection, dashboards, and calibration. Investigate integrity issues, run root-cause analysis, build automation in Python/SQL, and partner with Product, Engineering, and Operations to embed quality controls, train reviewers, and scale repeatable quality playbooks across programs.

Design, develop, deploy, and maintain MES platforms for semiconductor manufacturing. Build workflows, integrations (ERP, PLCs, SCADA, historians), databases for traceability and SPC, dashboards, and AI-enabled analytics. Collaborate with cross-functional teams, create documentation, ensure security/compliance, and support system lifecycle and scaling.

The Senior Data Engineer will design and maintain scalable data pipelines, lead data modeling, debug issues, and collaborate with teams to deliver reliable data solutions.

The Windchill Data Migration Developer develops and maintains data migration solutions within Windchill, conducts data analyses, supports system integration, and collaborates with teams to ensure quality and functionality of data migrations.

The Data Engineer will collaborate with global teams to design and implement data solutions, focusing on ETL processes and data validation within Allegion's analytics initiatives.