Top Data Engineer Jobs in Portugal

Lead and mentor a distributed data engineering team while architecting and building a next-generation, largely open-source data platform. Own hands-on POCs, pipeline design, schema and query optimization, ETL reliability, observability, testing, and CI/CD. Evaluate and recommend technologies, drive migration from vendor lock-in, and translate advertising and market research needs into robust technical solutions.

Design, implement, and maintain cloud-based data pipelines and architectures (ETL, data lake/warehouse). Advise clients on best practices, collaborate with product owners, mentor engineers, and deliver scalable distributed data solutions using cloud platforms and orchestration tools.

Design, implement, and maintain cloud-based data pipelines and architectures across AWS/Azure/GCP. Advise clients on best practices, partner with stakeholders to translate requirements, provide technical leadership, and mentor engineers while leveraging ETL/orchestration tools, data warehouses/lakes, databases, and programming languages for scalable data solutions.

Design, develop, and maintain batch and streaming data pipelines and ETL for large unstructured datasets. Build and operate CI/CD pipelines, containerize applications with Docker, deploy on Kubernetes, and collaborate with developers, data scientists, SMEs, and cyber analysts to deliver data management solutions.

Lead design and build of Snowflake-native medallion data architecture, ETL/ELT pipelines, master data and governance, and an enterprise semantic layer. Partner with Finance to produce reliable financial data products, optimize performance/cost, enforce data quality and compliance, mentor junior engineers, and support AI use cases and observability.

Design and build scalable Microsoft Fabric pipelines and lakehouse models, optimize Power BI semantic models and refresh strategies, enforce SDLC and CI/CD best practices, mentor teammates, and ensure SLA-driven, client-facing analytics reliability and performance.

Design and maintain enterprise-grade data architecture and production AI pipelines. Transform unstructured and disparate sources into normalized, queryable datasets in Snowflake. Lead data modeling, sharding, replication, indexing, and SDLC best practices while enabling data scientists and cross-functional teams through tooling, documentation, and architectural leadership.

Designs, builds, and optimizes data pipelines and architectures (ETL/ELT) to support analytics and ML teams. Assembles complex datasets, implements process improvements, collaborates with IT on AWS and Snowflake infrastructure, applies statistical techniques, supports reporting and analytics, and ensures compliance with financial regulations.

Lead design and ownership of a modern data platform: ingestion, Snowflake governance, pipeline reliability, migrations, data contracts, observability, and AI-enabled tooling. Partner with Analytics, Engineering, and vendors to deliver trustworthy data products and operate production pipelines.

Design, build, and maintain Power BI and MicroStrategy dashboards and reports; perform ETL and data integration from diverse sources; support IT operations through data analysis; ensure data accuracy and compliance with DoW STIGs and IL5/IL6/IL7; document solutions and train users; collaborate with stakeholders to translate requirements into visualizations.

The Mission Data Systems Engineer will conduct EW research, support system programming, and assist with data analysis during MD testing.

Design, build, and operate scalable batch and real-time data pipelines and feature store infrastructure to support recommendation systems. Own data ingestion, schema management, data quality, low-latency feature serving, and tooling. Collaborate with ML, backend, and product teams, mentor engineers, and drive platform architecture and reliability for terabyte-scale daily processing.

The Lead Data Science Engineer is responsible for engineering AI capabilities, managing data pipelines, and delivering ML engineering solutions, while ensuring data quality and optimizing existing systems.

Design, build, and maintain data ingestion and conversion pipelines using Node.js/Nest.js, MongoDB, and Next.js. Implement OCR/document processing, RESTful services, and ETL-style transformations for structured and unstructured data. Collaborate with cross-functional teams in an Agile environment to improve data quality, scalability, and performance.

Lead design, maintenance, and optimization of on-prem and cloud data platforms. Perform DBA duties for SQL Server, manage HA/DR and replication, troubleshoot performance, lead on-prem to Azure migrations, maintain Azure data services and Microsoft Fabric, optimize cloud cost/performance, implement monitoring, collaborate with architects and BI teams, and mentor junior engineers.

Design, build, and maintain large-scale data pipelines and ETL processes (NiFi, Kafka, AWS) using Python and Java. Create data models, automated cleaning, monitoring, unit tests, and warehousing solutions. Collaborate with engineering teams, use Docker and JIRA, and support analytics and data science consumers.

Design, build, and maintain large-scale data pipelines using NiFi, Kafka, Python, Java, and AWS. Develop ETL/warehousing, data models, automated cleaning, monitoring, unit tests, and SQL-based debugging. Containerize with Docker, collaborate via JIRA/Agile, and ensure scalable, observable data architecture for analytics and data science.

Own and drive the architecture and roadmap of ClickUp's data platform. Build scalable, reliable data pipelines and AI/ML infrastructure using AWS serverless, Snowflake, dbt, and Terraform. Lead cross-team technical initiatives, optimize cloud costs, establish engineering standards (observability, testing, CI/CD), mentor senior engineers, and influence org-wide architecture decisions.

Lead architecture and ownership of an enterprise Databricks/Azure data platform, design scalable ETL/ELT pipelines and integrations (HL7/FHIR), enforce governance and security for healthcare data, optimize performance/costs, drive CI/CD and IaC, and mentor engineers while partnering cross-functionally to deliver interoperable data solutions.

Design, build, and maintain scalable data analysis libraries, pipelines, and applications; collaborate on architecture and code reviews; prototype designs; apply data engineering and machine learning (including computer vision) to production problems; support mission-critical launch and Starlink systems.

The Principal Data Platform Engineer leads the architecture and development of the enterprise data platform, focusing on analytics, data science, and AI/ML capabilities. They establish standards for data quality and observability, design data ingestion and processing patterns, and mentor team members to enhance technical capabilities.

As a Senior Data Engineer, you will build complex data pipelines, optimize advertising data analysis, and collaborate with Data Scientists on data insights for business decisions.

Build and maintain backend services, cloud-hosted databases, and data pipelines to support analytics, reporting, and AI tools. Support Azure deployments, Power BI reporting, CI/CD, monitoring, and documentation while collaborating with Data Science, Finance, and IT stakeholders.

Design, build, and operate scalable batch and streaming data pipelines and a lakehouse on AWS. Implement ETL/ELT, CDC, metadata/catalog and governance, automated AWS provisioning (IaC), CI/CD for data pipelines, data quality and lineage, observability, and documentation while collaborating across teams.

Own day-to-day Snowflake administration and the Sigma semantic layer; manage ingestion (Fivetran), dbt modeling scope, reverse-ETL to Salesforce/HubSpot/NetSuite, data quality SLAs, reporting and dashboards, partner with managed data vendors, design automation and reproducible month-end financial analytics, and drive analysis and experiments for AdOps, Sales, and Finance.