Top Data Engineer Jobs in Portugal

Design, develop, and maintain web applications using .NET, AngularJS, NodeJS and MongoDB. Build and consume WSDL/SOAP/WCF web services, work with XML/XSLT, participate in all SDLC phases including architecture, development, testing, debugging, documentation, and maintenance.

Design, develop, test and implement IBM InfoSphere MDM solutions (v11.5.0.3) for pharma distribution. Perform architecture and design reviews, build J2EE/Java web services (servlets, EJB, XML), collaborate with global stakeholders, engage client-facing activities, and support deployments; travel as required.

Design, develop, and implement web applications using Microsoft .NET, AngularJS, Node.js and MongoDB. Build and consume web services (WSDL/SOAP/REST), XML/XSLT and WCF. Participate in all SDLC phases including architecture, development, testing, debugging, documentation and maintenance.

Design and develop Big Data solutions using the Hadoop ecosystem (Pig, Hive, MapReduce, HBase, Spark, Kafka, Oozie). Implement Java-based services and scripting, tune performance for large datasets, participate in full project lifecycle, and collaborate with stakeholders. Role requires extensive travel and strong communication.

Develop and maintain Hadoop-based big data solutions using Pig, Hive, MapReduce, HDFS, HBase, Spark, Kafka and related tools. Implement web services/APIs, performance tune large datasets, script in Java and shells, participate in full project lifecycle, and collaborate with stakeholders. Extensive travel and on-site work required.

Develop and maintain Hadoop/Big Data solutions using Pig, MapReduce, Hive, HBase, Spark, Kafka and related tools. Build Java-based components, scripts, and APIs; tune performance on large datasets; participate in full project lifecycle and collaborate with stakeholders.

Design, build, and maintain data warehouses, data marts, and OLAP solutions; develop ETL frameworks, data models, SSIS/SSAS/SSRS artifacts, and performance-tuned SQL Server databases to support analytics and visualization projects.

Design and develop Big Data solutions using Hadoop ecosystem (Pig, Hive, MapReduce, HBase, YARN, Spark, Impala, Kafka, Oozie). Implement Java and scripting-based pipelines, tune performance on large datasets, participate across SDLC phases, troubleshoot, and collaborate with stakeholders in a global delivery environment.

Develop ETL and data visualization solutions for a big data customer and partner experience transformation program. Build native Hadoop and Vertica ETL pipelines, collaborate with stakeholders, and support data integration and visualization deliverables for analytics teams.

Design, build, maintain, and test big data solutions and preprocessing/reporting pipelines. Collect, parse, manage, analyze, and visualize large datasets. Test and deploy machine learning models for scoring and prediction. Collaborate in agile teams to deliver scalable, reusable code and production-ready analytics on cloud platforms.

Design, develop, maintain and test scalable big data solutions. Build preprocessing and reporting pipelines, collect/parse/analyze/visualize large datasets, test and deploy machine-learning models on big data, and work in agile teams to deliver analytics solutions.

Design, develop, test and maintain scalable big-data solutions and workflows. Collect, parse, analyze and visualize large datasets; evaluate, test and deploy machine-learning models for scoring and prediction. Work in an agile team, automate tasks using scripting, and leverage Hadoop/Spark and AWS for production pipelines.

Design, develop, and release data ingestion and streaming solutions using Big Data technologies (Flume, NiFi, Kafka, Spark/Storm). Collaborate with stakeholders and distributed teams, follow agile practices, and support data warehousing and reporting efforts.

The Senior Data Engineer designs and maintains data pipelines and architectures to support enterprise analytics, ensuring data quality and integration across systems.

Design, build and deliver SAP-originated and non‑SAP data in formats consumable by non‑SAP tools and external B2B partners using SAP BO/Data Services, BW/BI. Support ETL, integration and data delivery processes.

Seeking four DataStage ETL developers with 2-5 years experience for a long-term (2-3 year) contract. Candidates will be screened via phone or Skype; internal candidates preferred.

Map source data entities and create transformation rules for ETL developers to load into target systems. Work with business clients to interpret rules. SQL and Excel required; telecom billing system conversion/integration (Amdocs) is strongly preferred.

Design and build IBM DataStage ETL jobs to extract, transform, and load data into 3NF and star schemas. Implement Slowly Changing Dimensions and Change Data Capture, write strong Oracle SQL, use QualityStage and parallel processing, create source-to-target mappings, write/execute test cases, and use Unix shell scripting. Collaborate with stakeholders and maintain data warehouse ETL processes.

Lead design and build of a cloud-based big data analytics platform: implement analytics infrastructure, integrate streaming and batch data, develop distributed processing pipelines, manage predictive analytics models, and apply machine learning and Bayesian methods. Work involves Scala on OS X and AWS, Java and Clojure, Kafka/Samza, NoSQL, and following TDD, Agile, CI/CD practices.

Design, build, and operate cloud-native data platform components for high-dimensional scientific data. Implement end-to-end solutions using Python and open-source tools, leverage cloud and DevOps tooling, enforce metadata, governance and testing practices, mentor junior engineers, and deliver reusable, scalable data-platform products for research teams.

Designs, builds, and supports secure data integrations, migrations, and ETL/ELT pipelines across ERP, student information systems, and the data warehouse. Works with stakeholders to gather requirements, automate data workflows, ensure data integrity, monitor integrations, document processes, and partner with security/privacy teams to maintain compliant data access. Supports system implementations and institutional reporting.

Lead design and scaling of enterprise data architecture and pipelines. Build and maintain ETL/ELT and CDC/streaming workflows, improve data quality and observability, own schema and warehouse modeling, implement governance (RBAC), and provide cross-functional technical leadership to enable trusted, scalable data for analytics and product teams.

Develop and improve inline metrology flows and failure-analysis methods for photonic quantum hardware. Build and analyze SPC charts, perform RCA, design experiments, coordinate with software and external partners, purchase and qualify metrology tools, and apply statistical analysis to improve yield and wafer performance.

Lead design, build, and optimization of the enterprise data warehouse and production data pipelines. Own platform architecture, integrate legacy systems (AS400), support Power BI semantic models (DAX), implement monitoring, CI/CD and governance, and mentor engineers to transition from consultant-run platforms to an internally managed, scalable data ecosystem.

Develop, deploy, and support large-scale distributed Big Data applications. Design multi-tier software, participate across the SDLC, perform database design and performance tuning, troubleshoot production issues, and collaborate with internal clients. Work primarily with Hadoop, Spark, Impala, Hive in Unix/Linux and Windows environments within financial/consumer banking contexts.