Top Data Engineer Jobs in Portugal

Develop and maintain Python and SQL processes for acquiring, transforming, normalizing, and loading large spatial datasets into databases. Evaluate commercial and open-source data quality, interpret product specifications, update ETL workflows, and support continuous geocoding data quality improvements. The role collaborates with product teams and manages multiple priorities in a fast-paced environment.

Design, build, and operate complex Apache Airflow workflows, Snowflake and dbt data transformation pipelines, and distributed data science inference systems across multi-cloud environments including AWS and GCP. Collaborate with an experienced data engineering team while applying systems engineering and product lifecycle principles.

Build and maintain scalable data platforms, pipelines, and ETL/ELT workflows for structured and unstructured data. Develop scripts and programs to convert data into usable formats, support platform operations, and collaborate with analysts, engineers, developers, and data consumers in agile environments. Projects support missions including fraud detection, cancer research, and national intelligence.

Build and own Stuut’s data infrastructure, including ingestion pipelines, canonical data models, semantic layers, event pipelines, quality testing, observability, and DataOps practices. Partner with product, engineering, and ML teams to deliver reliable datasets, dashboards, KPIs, and insights. This foundational role will establish the company’s data architecture and scale it as customer adoption grows.

Engineer and maintain mission-relevant data ingest and distribution pipelines across multiple networks. Configure ETL workflows, COTS/GOTS applications, databases, cloud systems, and CI/CD infrastructure. Troubleshoot production systems, hardware, protocols, and network connectivity while ensuring data reliability, low latency, and integrity. Collaborate with software developers, systems administrators, external providers, users, and stakeholders. Maintain system documentation, diagrams, monitoring, and operational workflows in an agile environment.

Architects, develops, and optimizes scalable data pipelines and cloud-native platforms. Leads data engineers in integrating structured and unstructured data across secure environments, establishes engineering standards, ensures data quality, and supports analytics, reporting, and mission-critical decisions. Uses ETL, distributed systems, streaming architectures, cloud services, and access controls to deliver reliable enterprise data infrastructure.

Builds and maintains reliable, scalable, secure data platforms and cloud infrastructure. Responsibilities include troubleshooting Tier 3 production issues, designing data ingestion and transformation workflows, implementing CI/CD, monitoring systems, and supporting enterprise data operations. The role may involve Kubernetes, Kafka, NiFi customization with Java, AWS services, and classified Intelligence Community environments.

Build and operate Block’s data platform, including warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop reliable Python services, developer tools, and Terraform infrastructure for petabyte-scale data. Partner with data practitioners and product teams, establish engineering standards, provide technical direction, and mentor engineers while ensuring security, reliability, observability, usability, and data governance.

Build and operate a scalable data platform supporting warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop Python services, Terraform infrastructure, and developer tools for petabyte-scale data. Partner with data practitioners and product teams, establish security and reliability patterns, set technical direction, improve engineering standards, and mentor engineers.

Designs and operates scalable batch and streaming data pipelines and AI-ready data products across Databricks, Snowflake, Kubernetes, and cloud services. Develops governed data assets, semantic models, search and retrieval capabilities, and data quality processes. Supports Snowflake Cortex and Databricks initiatives, production troubleshooting, orchestration, performance optimization, CI/CD, and observability. Partners with business and technical teams on roadmaps and adoption, evaluates AI-assisted engineering tools, mentors engineers, and establishes reusable platform patterns.

Design and build data models, data warehouses/lakes, and automated ETL pipelines; integrate diverse data streams; structure unstructured data; develop data collection frameworks, standards, governance, and analytic tools; manage and troubleshoot data feeds in complex, multi-enclave environments to support cyber and operational intelligence products.

Supports a multi-year migration to a Snowflake-based business intelligence platform. Performs business and systems analysis, reporting requirements development, dashboard and BI Publisher report creation, RPD and metadata modeling, ETL development, SQL optimization, data transformation, troubleshooting, documentation, and production support. Collaborates with functional, database, security, PeopleSoft, and BI teams to improve data quality, performance, governance, and reporting capabilities.

Designs, builds, and manages a Snowflake-based business intelligence platform using dbt, SQL, data modeling, pipelines, and transformation tools. Performs business and systems analysis, fit-gap analysis, security and permissions testing, technical specifications, solution development, system and user acceptance testing, troubleshooting, documentation, training, and risk management. Collaborates with reporting, functional, PeopleSoft, database, security, and other project teams to modernize citywide analytics and data sharing.

Build and productionize a robotics data platform that ingests sensor data, validates and curates datasets, supports annotation workflows, and improves data quality and diversity. Develop automated labeling methods using computer vision and vision-language models, operate live pipelines, improve observability, and collaborate with research and annotation teams. The role involves taking early-stage systems to scalable production and supporting field deployments.

Develops and supports secure data integrations, migrations, and ETL/ELT pipelines across ERP, student information, and data warehouse systems. Builds API, connector, batch, and file-transfer integrations; transforms and validates data; monitors workflows and resolves processing issues. Collaborates with business, technical, security, and analytics stakeholders to gather requirements, document data flows, support reporting, and improve system interoperability. The role requires regular hybrid campus presence in Golden, Colorado.

Lead the architecture, development, governance, and operation of scalable data platforms, pipelines, schemas, databases, and warehousing infrastructure. Guide data acquisition, transformation, cataloging, and integration across cloud and local environments while ensuring reliability, security, performance, and data quality. Collaborate with product and engineering leadership, recommend data solutions, establish technical standards, and mentor engineering teams.

Lead the design, development, deployment, and operation of scalable data pipelines, APIs, services, and healthcare analytics applications. Translate business and analytical requirements into reliable production solutions, establish technical standards and architecture, troubleshoot issues, improve performance, document designs, coordinate platform changes, and provide technical leadership and mentorship to data engineers.

Build and operate a scalable data platform supporting pipelines, reporting, and analytics across business teams. Responsibilities include defining canonical data models, implementing workflow orchestration with tools such as Airflow, improving platform infrastructure, troubleshooting complex data and system issues, enforcing data security controls, and mentoring junior engineers. The role requires strong software engineering, cloud, infrastructure, communication, and data pipeline expertise.

Creates and manages data connections, validates and transforms incoming portfolio data, and normalizes external datasets into Clearwater’s standardized format. Automates monitoring and reporting, integrates APIs and FTP connections, and improves auto-reconciliation through data analysis and process enhancements. Collaborates with Operations and Development, troubleshoots data-feed issues, documents workflows, communicates technical concepts to nontechnical stakeholders, and provides light on-call support.

Designs and evolves an enterprise Azure-based Lakehouse platform using Microsoft Fabric and Azure Databricks. Builds metadata-driven ingestion, ELT, CDC, orchestration, Spark/PySpark transformations, semantic models, and governed Bronze, Silver, and Gold data layers. Integrates enterprise systems across ERP, CRM, construction, manufacturing, HR, and operations while establishing standards for data quality, lineage, security, observability, performance, and cost optimization. Partners with stakeholders to deliver trusted data products and provides technical leadership across architecture and engineering.

Build and scale high-performance data pipelines and systems supporting a biomedical knowledge graph. Develop tools for ingesting, transforming, and delivering biomedical data; improve cloud-native workflows, reliability, and performance; and promote engineering practices including code reviews, automated testing, continuous integration, monitoring, and root-cause analysis. Collaborate with DevOps, data, ontology, QA, and application engineering teams. The role requires onsite work in Redwood City.

Designs and maintains scalable infrastructure for ingesting, processing, storing, and serving large volumes of legal and financial document data. Responsibilities include building data pipelines and backend services, improving databases and schemas, implementing governance and GDPR compliance, supporting machine learning workloads, leading technical initiatives, and mentoring engineers.

Develops and operates integrated data systems supporting New Glenn certification and launch services. Responsibilities include ensuring data quality, maintenance, sharing, governance, customer engagement, training metrics, and certification support. The role collaborates with New Glenn teams, NASA, and U.S. Space Force partners; plans technical products, communicates results, enforces data-marking practices, manages resources, and provides product ownership in a fast-paced aerospace environment.

Build and maintain factory data pipelines, structure production datasets, analyze manufacturing performance, develop dashboards and metrics, and prototype statistical or machine learning solutions. Collaborate with operations, quality, engineering, and program management teams to turn business questions into measurable analyses. Contribute clean, tested, documented code, identify data quality issues, and help govern factory data.

Leads global engineering standards, testing, and certification programs for advanced data center cooling technologies. Serves as a regional or global SME, develops test methods and equipment, performs complex thermal and fluid testing, and represents the organization in industry standards activities. Responsibilities include cold plate and immersion cooling validation, heat reuse certification, refrigerant and dielectric compatibility assessments, leak detection integration, regulatory alignment, client issue resolution, technical publications, continuous improvement, and workforce training.