Top Data Engineer Jobs in Portugal

Design, develop, and support cloud-based analytics (Power BI, Snowflake). Build ELT/ETL pipelines, enterprise data models, and Power BI reports. Migrate legacy BI, validate data integrity, enforce security/governance, troubleshoot issues, train users, and support analytics initiatives across the business.

Serve as first point of contact for customers using Agentforce and Data 360, troubleshoot technical issues, provide feature guidance and best practices, manage customer expectations, create and maintain knowledge content, participate in training, and escalate complex issues to internal teams to ensure customer success.

Lead design and delivery of production data platforms, pipelines, and analytics. Architect Snowflake/Databricks solutions, build ETL/streaming ingestion, implement dbt transformations, data quality, observability, and governance, support BI and AI/ML feature/data pipelines, and mentor engineers while driving DataOps and platform best practices.

Design, build, and operate production LLM-driven agents that discover and verify business web presence, link people to entities, score legitimacy/risk, and maintain shared agent infrastructure (tool registry, eval harness, instrumentation). Own model selection, prompt/tool engineering, eval methodology, and cost/latency optimization for enrichment pipelines.

Design, build, and operate reliable, scalable backend services and platform capabilities for monetization (pricing, billing, ads, payments). Own architecture, integrations, correctness, observability, and operational excellence. Lead cross-functional technical projects, write RFCs, mentor engineers, and deliver reusable developer tools and data products for product, finance, and GTM teams.

Build, test, and deploy scalable data platform services supporting ETL/ELT, streaming, and analytics. Collaborate with global teams, troubleshoot production issues (on-call), optimize performance, and maintain documentation and observability for platform reliability.

Design, build, test, and deploy scalable data platform services (ETL/ELT, streaming, batch) using cloud and distributed processing frameworks. Support production on-call, collaborate with global teams, improve performance, and maintain platform documentation and observability.

Lead design, development, and administration of enterprise Power BI reporting, semantic models, and Azure-based data pipelines. Deliver executive dashboards, KPIs, advanced analytics, and governance; mentor teams and modernize BI capabilities while ensuring performance, security, and data quality across the organization.

Build and operate production Kubernetes-based compute platform for large-scale data and ML workloads. Improve cluster reliability, GitOps delivery, multi-tenant scheduling, resource isolation, GPU workload orchestration, and reusable batch/workflow systems for petabyte-scale processing while contributing to QMS and continuous improvement.

Design, build, and optimize scalable ETL/ELT data pipelines and data platforms for AI and analytics. Work with large structured and semi-structured datasets, ensure data quality and reliability, implement data models, support healthcare data ingestion and interoperability (EHR/EMR, HL7/FHIR), and maintain CI/CD, testing, and monitoring best practices.

As a Data Engineer II, you will develop and manage data lakes and warehouses, monitor database performance, optimize queries, and automate tasks using infrastructure as code.

Design, build, test, and maintain production-ready, scalable API services and platform solutions using microservices and containerization. Collaborate with engineers, Data Engineers, CloudOps and Product to deploy and operate services on cloud platforms, ensure observability and readiness, and participate in Agile lifecycle activities.

Partner with business leaders to define data problems, process and analyze complex datasets, build predictive models and ML algorithms, perform EDA and A/B testing, create dashboards and visualizations, and work with data engineers to build reliable data pipelines to inform strategy.

Design, develop, and prototype compliance and business-processing analytics and ML/AI tools. Automate compliance functions, build and monitor machine learning models (including Random Forests and feature development), integrate and test algorithms/POCs, instrument metrics and monitoring, and produce and review technical documentation.

Design, deploy, and maintain scalable cloud data infrastructure on AWS and GCP. Build and automate data ingestion/processing frameworks, CI/CD pipelines, and cloud automations. Optimize and troubleshoot data pipelines and system performance, ensure security in transit and at rest, and collaborate with data engineering, data science, and security teams. Mentor peers and follow agile practices.

Design, build, test, and maintain ETL pipelines, data warehouse and BI solutions. Partner with business users, perform performance/regression testing, review code, troubleshoot data issues, and oversee production deployments.

Lead the development and operation of a data lake for cyber operations, design schemas and indexes, build and evolve ETL pipelines, mentor engineers, and drive technical initiatives.

The role involves leading the development of data lakes, designing schemas, building ETL pipelines, and mentoring engineers while ensuring data quality and performance.

The Senior Data Engineer will design and maintain data processing systems, enhance ETL components, and ensure data security and integrity while mentoring junior staff.

Develop and optimize Hadoop/Big Data solutions using Java MapReduce. Work with Hadoop ecosystem tools (Pig, Hive, HBase, Oozie), NoSQL databases (Cassandra/MongoDB), reporting tools (Tableau/Platfora), Unix environments, and optimize ETL jobs. Execute major projects and communicate effectively with stakeholders.

Design, develop, debug and tune Hadoop-based ETL using HDFS, Pig, Hive, HBase, Sqoop and Java. Provide technical oversight to the Hadoop team, write/modify shell or Python scripts, liaise with application teams, perform performance tuning and troubleshooting, and provide on-call weekend support.

Develop, debug, and optimize Hadoop-based data solutions using Pig, Hive, Sqoop, HBase and Java. Write and maintain shell/Python scripts, perform performance tuning, apply Big Data architecture/design patterns, guide the Hadoop team, coordinate with application teams for issue resolution, and provide on-call weekend support.

Design, build, and tune scalable data pipelines and streaming platforms using open-source tools (Kafka, NiFi, Hive, MapReduce) and NoSQL/SQL datastores. Automate ingestion, transformation, and augmentation of structured and unstructured data, collaborate with analysts, developers and data scientists, and ensure high availability and performance for analytics and transactional systems.

Develop and maintain Big Data applications using Java/Spring and Python on MapR HDFS with MapReduce, Pig, and Hive. Design NoSQL data models in HBase, participate in SDLC activities, configuration management, code reviews, and collaborate with offshore teams. Apply credit risk/fraud/payments domain knowledge and use tools like Jira, Maven, and SOAP UI.

Design, develop, and support Big Data solutions on Teradata Aster and Hadoop platforms. Build ETL pipelines, data mining, reporting, and predictive analytics; write efficient code for large/unstructured datasets; translate business use cases to production; mentor users; contribute to Big Data roadmap and standards.