Top Data Engineer Jobs in Portugal

Lead data engineering teams to design, build, and maintain scalable cloud-native data pipelines, data platforms, and data products using Snowflake, Databricks, Airflow, and modern architectures. Optimize ETL/ELT, SQL, and transformations for analytics, reporting, and AI use cases; ensure data quality, governance, observability, and stakeholder alignment. Produce documentation, runbooks, and present technical solutions to business and technical audiences.

Lead a team building large-scale ML model evaluation and orchestration frameworks for autonomous vehicles. Own data analysis workflows, dataset creation, statistical model evaluation, regression reporting, and tool development (AWS Kubernetes orchestration, ReSimulation). Provide technical leadership, mentorship, and manage project timelines and deliverables.

As a Senior Controls Engineer, you will design, deploy, test, and maintain control systems, ensuring quality through collaboration with clients and team members.

Build and maintain high-throughput C++ recording systems and Python data services for vehicle sensor and telemetry data. Work on data transfer, ingestion, validation, format/versioning, indexing, compression, and efficient access for replay, analytics, and ML while operating under vehicle resource constraints and contributing to quality management.

Build and manage automated ETL integrations from customer EMRs, billing, and warehouses into Caris systems. Lead data discovery, validation, and architectural design for clinical informatics and BI. Gather technical requirements, implement access via FHIR/HL7/APIs or direct DB, assemble large clinical datasets, and deliver dashboard-ready data for business users.

Design, build, and maintain scalable, secure cloud data pipelines and integrations. Develop APIs and modular components, apply generative AI to pipelines, enforce data governance and compliance for PHI/PII/PCI, mentor engineers, collaborate with analysts and data scientists, and ensure production reliability using containerized deployments and DevSecOps/Agile practices.

Design, build, and operate a Snowflake-centered cloud data platform: ingest with Fivetran, transform with dbt, orchestrate with Airflow/Astronomer, ensure observability and data quality, deliver CI/CD workflows, troubleshoot pipelines, guide Cortex Code adoption, and mentor junior engineers while partnering with cross-functional teams.

Deliver ServiceNow reporting and analytics: define KPI standards, build dashboards/scorecards, maintain reporting datasets and integrations, automate data quality checks, provide operational insights, support release and operations reporting, and partner with global platform and product stakeholders for data-driven decisions.

The Cyber Data Science Engineer analyzes large cybersecurity data sets, provides analytics, develops data-driven solutions, and supports compliance reporting while collaborating with team members.

As a Software Engineer, you will build core data systems, collaborate on new features, and improve team productivity within a hybrid working environment.

Design, build, and optimize scalable batch and streaming data pipelines. Model and process structured and unstructured data, ensure production reliability and observability, apply ML techniques for insight extraction, and drive data strategy while adopting modern tooling and IaC practices.

Lead design, build, optimization, and operation of scalable Databricks-based batch and streaming data pipelines for healthcare programs. Ensure DataOps, data quality, lineage, observability, CI/CD, and compliance with CMS and federal healthcare regulations. Collaborate with architects, data scientists, and stakeholders, troubleshoot production issues, and mentor junior engineers.

Design, build, and optimize scalable end-to-end data pipelines and Snowflake data warehouses. Develop BI solutions (Power BI/Tableau/Cognos), enforce data quality/governance, integrate investment data vendors, collaborate with stakeholders, mentor junior engineers, and follow SDLC/DevOps best practices.

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.

Build, train, fine-tune, evaluate, and deploy machine learning and LLM models for production. Create monitoring, evaluation, and feedback tooling, evaluate new techniques, and collaborate cross-functionally to ship ML-powered features.

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, 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 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.

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.

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.

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.

Own and evolve the data platform: architect, build, and maintain data models, pipelines, and access layers. Ensure data quality, governance, and reliability; monitor and optimize infrastructure; provide technical leadership, code reviews, and collaborate with cross-functional teams to deliver scalable data solutions for operations and analytics.

Build quantitative analytics and electronic trading products by combining data analysis and full-stack web development. Develop dashboards and tools using ELK, JS frameworks, and SQL databases; write complex queries against Sybase/Sybase IQ/Rainstor and perform Excel-based analysis. Work in a small, entrepreneurial team to deliver production-ready analytics and web applications. C#/.NET and unstructured data exposure are nice-to-haves.

As a Senior Data Engineer, you will design and maintain data systems for Aircapture, focusing on building data pipelines and making architectural decisions to support climate technology.