Top Data Engineer Jobs in Portugal

Develop, curate, and publish authoritative geospatial data products in ArcGIS Portal; build Python data-processing pipelines; and create Tableau dashboards and web maps. Manage metadata, hosted feature layers, and data discoverability while partnering with mission users to transform large spatial and tabular datasets into operational visualizations and automated workflows.

Build, scale, and monitor end-to-end data pipelines and infrastructure powering AI products; implement reporting solutions; optimize data models and queries; mentor teammates and support ML model productionization.

Designs, builds, deploys, and maintains scalable data architectures, databases, ETL/ELT pipelines, API integrations, and cloud data solutions in AWS GovCloud. Migrates on-premises databases to cloud platforms, optimizes data models and performance, implements governance and security controls, and supports reporting and analytics. Collaborates with architects, data scientists, and stakeholders while documenting systems and conducting integration, validation, cost, and risk assessments.

Designs, develops, and maintains scalable AWS data pipelines and infrastructure. Responsibilities include data ingestion, ETL transformation, storage, orchestration, monitoring, optimization, troubleshooting, data quality, governance, security, and privacy. The role partners with stakeholders to develop data solutions and supports reliable, accessible data for decision-making.

Design and deliver enterprise-scale data models and analytics-ready datasets in Snowflake; build reliable ELT/ETL pipelines (batch and near-real-time); enforce data quality, observability, and secure handling of PII; optimize performance and publish curated data to downstream systems while collaborating with product, operations, and engineering teams.

Build and maintain scalable Microsoft Fabric data pipelines, ingestion frameworks, Delta Lake architectures, dimensional models, and Power BI semantic models. Optimize performance, refresh strategies, capacity usage, monitoring, and data quality while supporting client analytics SLAs. Collaborate with BI developers, analysts, and stakeholders to translate requirements into features, participate in agile ceremonies, and follow Git, CI/CD, code review, and SDLC practices.

Designs and maintains enterprise data models, metadata, taxonomies, governance standards, quality rules, lineage documentation, and integration mappings for NASA’s external engagement platform. Supports CRM workflows, analytics-ready data, dashboards, AI data preparation, and cross-agency interoperability. The role also translates business needs into technical data solutions and coordinates documentation and stewardship across teams.

Designs, builds, and maintains scalable data pipelines, relational databases, data integrations, and data warehousing solutions. The role develops ELT processes, ensures data quality and governance, troubleshoots pipeline and database issues, and documents workflows. It collaborates with Data Operations, Quality Engineering, Business Intelligence, architects, and subject matter experts to deliver reliable data assets aligned with business needs.

Build and operate production data pipelines and warehouse models for a global energy trading platform. Develop Python pipelines orchestrated with Prefect, create tested Snowflake models with dbt, migrate legacy Oracle systems, integrate diverse data technologies, and implement quality, freshness, monitoring, and alerting controls. The role also supports AI-ready data, AWS services, platform documentation, and direct collaboration with analysts and desk users.

Designs, implements, and sustains secure mission data pipelines for the Department of the Air Force’s DIFC2 program. Responsibilities include mission data architecture, interface and schema definition, ETL and transformation development, API integration, monitoring, documentation, and RMF compliance. The role requires collaboration with government, cybersecurity, and mission partners to deliver reliable, interoperable data flows in a defense environment.

Develop and maintain data pipelines for GEOINT datasets, transform and standardize data for machine learning environments, assist with data service development, document workflows, analyze data, and support data quality. Collaborate with senior engineers and scientists on Department of War artificial intelligence initiatives while communicating findings and adapting to changing priorities.

Designs, builds, and maintains cloud data pipelines and ETL/ELT processes supporting VA healthcare analytics. Responsibilities include patient matching, record linkage, data harmonization, quality management, documentation, performance optimization, and pipeline support. Collaborates with analysts and stakeholders to develop scalable solutions and Power BI reports using Databricks SparkSQL. The role requires federal healthcare data experience, strong SQL or Spark SQL skills, and the ability to obtain a VA Public Trust clearance.

Build and maintain data pipelines, reporting solutions, Power BI dashboards, semantic models, and KPIs. Clean, transform, validate, and reconcile data from ERP, Microsoft, Excel, third-party, and operational sources. Automate repetitive reporting, troubleshoot data issues, support recurring and ad hoc requests, document business logic, and collaborate with departments to deliver reliable reporting and process improvements.

Build and optimize data pipelines, backend services, forecasting systems, dashboards, and automated workflows supporting Starlink ground-network inventory, logistics, deployment, and reliability. Integrate ERP/MRP and logistics systems, manage hardware demand forecasting, improve supply-chain processes, monitor operational metrics, and support emergency deployments. The role requires collaboration across engineering, infrastructure, logistics, and program teams, with up to 25% travel and occasional extended or weekend hours.

Lead the modernization of a healthcare data platform from an MSSQL XML object store to a scalable AWS architecture. Evaluate AWS storage and query services, design SQL reporting layers, architect data migration and metadata strategies, optimize performance and cost, and build CI/CD and infrastructure-as-code pipelines. Partner with business stakeholders, analysts, and C#/.NET engineers to deliver accessible data models and reliable integrations. Document architecture, data flows, and migration processes while supporting healthcare data and compliance requirements.

Designs and leads enterprise-scale Snowflake data engineering solutions, including data warehouses, ELT pipelines, data models, cloud integrations, orchestration, and performance optimization. Builds scalable batch and streaming pipelines, APIs, data quality controls, automated tests, and reusable engineering components. Partners with architecture, security, governance, DevSecOps, and business stakeholders while supporting data analysis, application design, coding, deployment, and production maintenance.

Designs, builds, maintains, and scales enterprise data infrastructure for ingestion, processing, extraction, and analysis. Responsibilities include ETL development, data cleansing and normalization, data modeling, warehousing, anomaly detection, statistical modeling, and natural language processing module development. The role also troubleshoots complex data systems and fulfills data-related business requests.

Supports the design and development of scalable end-to-end data pipelines and cloud data platforms. Responsibilities include improving data reliability and quality, implementing data management practices, supporting automation and process improvements, ensuring secure and cost-effective solutions, and recommending system enhancements. The intern collaborates with global teams and gains hands-on experience in data engineering, project coordination, and innovation management.

The Principal Data Engineer designs and builds scalable cloud-native data platforms, pipelines, frameworks, and governed data products supporting analytics, reporting, AI, and operational workloads. Responsibilities include Databricks, Spark, Delta Lake, Azure, SQL Server, batch and streaming processing, data integration, performance optimization, governance, modernization, troubleshooting, architecture reviews, and mentorship. The role provides senior technical leadership without direct people management and supports insurance-domain data across policy, claims, billing, finance, and regulatory functions.

Supports implementation and stabilization of inbound and outbound healthcare data processes. Ingests, transforms, validates, and reconciles Medicaid claims and eligibility feeds from Gainwell, Arcadia, DHCS, and other sources. Establishes data-quality, refresh, completeness, and reconciliation controls for PRISM, case creation, and reporting. Supports Atrezzo interfaces, data exchanges, production analytics, troubleshooting, root-cause analysis, stakeholder communication, and implementation workstreams.

Build and maintain enterprise data platforms, data lakes, warehouses, dimensional models, ETL workflows, integrations, KPIs, and analytics solutions using Azure, Oracle, and BI technologies. Extract, cleanse, transform, and analyze data; develop SQL queries and data models; monitor and troubleshoot jobs; support business requirements; perform AI and machine learning proofs of concept; document solutions; and collaborate with IT, business, and analytics teams.

Design, build, and maintain scalable data pipelines, warehouses/lakes, and platforms. Lead multidisciplinary teams to implement ETL/ELT (batch and streaming), optimize data lake performance, enforce data governance, and support analytics and ML use cases on cloud and on-prem environments.

Design, build, and maintain reliable ETL/ELT pipelines, data models, warehouses, lakes, and databases. Implement data quality, monitoring, cleansing, and security practices while supporting AI-ready data capabilities and analytics initiatives. Collaborate with architects, analysts, business stakeholders, vendors, and consultants to translate requirements into scalable technical solutions. Document processes, troubleshoot issues, optimize workflows, and manage multiple projects in a deadline-driven environment.

Build and maintain scalable ETL/ELT data pipelines, write production Python and Node.js code, develop data models, schedule and monitor workflows, optimize performance, ensure data quality, troubleshoot issues, collaborate with analysts and product teams, and document solutions.

Designs and maintains scalable data architectures, ETL workflows, batch and real-time pipelines, and SQL/NoSQL storage solutions supporting intelligence operations. Ensures data quality, governance, security, compliance, and performance across structured and unstructured intelligence datasets. Documents schemas and data lineage, collaborates with analysts and data scientists, and participates in technical and mission-planning forums.