Top Data Engineer Jobs in Portugal

Own enterprise-scale data architecture and engineering for Xometry’s data platform, including real-time partner integration pipelines connecting manufacturing systems. Design scalable batch and streaming systems, data models, governance, observability, testing, and CI/CD practices. Lead multi-quarter technical roadmaps, collaborate across engineering, product, analytics, machine learning, and external partners, and mentor engineers. Support the DFM AI and IQE integration across Teamcenter, Designcenter, and related systems.

Build, deploy, and operationalize complex data pipelines and solutions using modern data platforms and ETL tools. Design data architectures, integrate sources, improve data quality, and support AI, machine learning, and business intelligence initiatives. Analyze and resolve complex data defects and incidents, apply governance and security practices, and serve as a data engineering subject matter expert. Guide team members, educate business users, communicate technical concepts, and provide technical leadership across enterprise data projects.

Build automated validation, reconciliation, anomaly detection, and test automation for cloud billing data across AWS, Azure, and Google Cloud. Investigate and resolve data-quality issues, automate preventive checks, document provider billing models, support customer-facing data questions, and use AI tooling to accelerate investigation and anomaly triage.

Build and lead Cognite’s enterprise data warehouse, semantic layer, data pipelines, integrations, and business data models. Use Azure, Microsoft Fabric, Power BI, Python, SQL, APIs, and Cognite Data Fusion to deliver reporting and AI-ready data solutions. Establish data governance, security, privacy, and quality standards while partnering with Finance, Sales, Marketing, HR, Legal, Engineering, and other stakeholders.

Build and operate production data pipelines across Oracle, Talend, and Apigee using SQL, PL/SQL, Java, and Python. Integrate acquisition and financial data, develop reusable data products and analytics datasets, maintain REST APIs, migrate legacy data, optimize workflows, and implement validation, governance, testing, documentation, and database design practices. Support Navy acquisition transformation in an IL-4/5 government environment.

Leads the design, governance, and integration of mission-focused data ontologies, knowledge models, taxonomies, and standards. Collaborates with analysts, engineers, architects, and data owners to establish interoperable data practices, support standards adoption, and integrate models into enterprise tools and workflows. Produces monthly posture reports and guides data architecture and approval processes for intelligence data enterprises.

Develop data models, algorithms, visualizations, workflows, and systems engineering documentation for an intelligence customer’s AI and risk management capabilities. Integrate and organize structured and unstructured data, validate requirements and controls, support cloud infrastructure in high-security environments, and translate business needs into technical solutions. Collaborate across sponsor organizations, conduct link analysis, identify technology gaps, and communicate technical findings through briefings and reports.

Build and maintain Oracle EBS data replication and integration pipelines using GoldenGate and Qlik Replicate for Advana. Monitor performance, troubleshoot failures, optimize throughput and latency, document data flows, support BI dashboards, and ensure compliance with federal data governance and DoD cybersecurity requirements. Coordinate upgrades, patching, migrations, and collaboration with reporting, security, and IA teams.

Builds and maintains reliable data solutions, datasets, transformations, and enterprise data warehouse infrastructure. Responsibilities include data quality profiling, cleansing, normalization, modeling, testing, CI/CD, performance optimization, anomaly analysis, and troubleshooting. The role partners with data architecture teams, supports reporting and KPI accessibility, and follows PII and organizational risk standards. It requires onsite work in West Bend, Wisconsin, with some hybrid flexibility.

Leads development of Navanta’s secure data backbone, including lakehouse architecture, bank-system ingestion, CDC pipelines, semantic modeling, data quality, reconciliation, observability, governance, and lineage. Partners with AI/ML, security, and platform teams to deliver reliable, queryable data products for financial institutions. Owns data contracts, access controls, regulatory data handling, pipeline SLAs, bank onboarding, and on-call reliability operations.

Design, build, and maintain ETL/ELT pipelines and SSAS tabular models. Develop complex T-SQL queries and Power BI reports. Ensure data quality, optimize performance, and support migration of legacy systems into Microsoft BI environments while collaborating with stakeholders.

Design and modernize scalable data engineering, BI, and data warehouse solutions. Build enterprise ETL pipelines using Azure, Databricks, Informatica PowerCenter, SSIS, and related technologies. Develop complex T-SQL, tune database performance, test ETL solutions, troubleshoot data issues, and collaborate cross-functionally. Provide technical guidance to Data Engineers while supporting data modernization, analytics, reporting, and operational efficiency.

Supports government space and counterspace intelligence operations by collecting, integrating, validating, maintaining, and analyzing large datasets. Develops automated data workflows, scripts, databases, dashboards, reports, and visualizations; establishes data quality and governance practices; analyzes RF and signals data; and supports collection management, mission planning, operational reporting, and readiness assessments. Collaborates with government stakeholders, mission partners, and technical teams.

Designs, implements, secures, monitors, and optimizes AWS cloud-native data engineering solutions supporting analytics, AI/ML, LLMs, and agentic services. Builds ingestion, ETL, transformation, data-store, API, search, monitoring, FinOps, and security capabilities. Prepares model-ready datasets, applies DoD Zero Trust and NIST controls, supports authorization activities, documents architectures and costs, and collaborates with government, data science, cybersecurity, and cloud engineering stakeholders onsite in a classified environment.

Own and evolve Worldly’s production data lake, Postgres warehouse, CDC and streaming pipelines, dbt transformations, orchestration, BI access controls, and graph integrations. Maintain reliable, governed analytics infrastructure using Iceberg, Trino, Dagster, Terraform, and AWS. Support production generative AI workflows involving embeddings, similarity search, extraction, and classification. Responsibilities include data quality, monitoring, security, incident response, disaster recovery, schema governance, and collaboration with data science and analytics stakeholders.

Designs, administers, and optimizes data systems supporting FSA IAM applications. Develops migration plans from legacy AIMS and PAS systems, creates data models, mappings, layouts, dictionaries, and integration processes, and supports analytics and fraud detection. Manages database configuration, performance tuning, monitoring, backups, capacity, secure data handling, encryption, network data flows, token management, and documentation while collaborating with development, security, and operations teams.

Design, build, and operate large-scale data platforms and Spark/PySpark pipelines. Enable data integration, modeling, quality, and observability. Build MCP servers and AI-augmented tooling, mentor engineers, and lead cross-functional projects to deliver reliable data products.

Design, build, and operate scalable, secure data platform infrastructure for ingesting, processing, cataloging, and accessing petabytes of data. Improve Spark/Databricks reliability and developer experience, build ingestion/replication systems, develop internal libraries and tooling (Go/Python), and collaborate with cross-functional teams to support analytics, ML, and customer-facing data products.

Responsible for maintaining and supporting critical data center operations, including hardware installation, troubleshooting, and collaboration with IT teams.

Lead end-to-end design and implementation of GTM-facing software and data products. Build features in Go/TypeScript/SQL, operate services on Cloudflare Workers and Kubernetes, own the data foundation and signals for sales, run cross-functional projects, participate in on-call incident response, and collaborate with Sales/Marketing/DevRel using AI to accelerate development.

Leads an engineering team responsible for designing, building, and operating data security products and controls. Provides technical direction, hands-on engineering leadership, and delivery ownership across DLP policy, data discovery and classification, data access controls, policy-as-code workflows, automation, integrations, testing, deployment, reliability, and operational support. Translates data security requirements into scalable solutions while mentoring engineers and driving adoption of secure engineering practices.

The role involves building data infrastructure, maintaining ETL pipelines, collaborating with analysts, and improving data models and processes.

The Senior Data Center Linux Engineer manages Linux servers, troubleshoot issues, develops automation scripts, ensures secure configurations, and deploys containerized applications.

The Sr. Network Data Center Engineer will design and manage network infrastructure, ensuring high availability, security, and performance for virtual environments and storage systems.

Designs, builds, and maintains an ontology-grounded enterprise semantic map and metadata graph. Develops automated metadata ingestion, ETL pipelines, API integrations, graph database schemas, lineage and provenance models, and graph queries. Aligns data assets with enterprise ontologies, governance requirements, and mission metadata. Enables semantic search and AI agents, optimizes graph performance, documents architecture, and mentors engineers. Requires production data engineering, graph database, systems integration, and graph query experience, plus an active TS/SCI clearance.