Top Data Engineer Jobs in Portugal

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.

Supports development and maintenance of an ontology-grounded enterprise metadata graph. Responsibilities include automating data-source discovery, ingesting technical metadata, integrating APIs and catalogs, mapping assets to ontologies and provenance layers, maintaining graph databases, supporting lineage and governance metadata, writing basic graph queries, and enabling semantic search and AI-agent workflows. Collaborates with senior engineers and AI teams to connect data assets to enterprise mission workflows.

Design, implement, and maintain secure, scalable enterprise database and geospatial data platforms for mission-critical Defense and Intelligence systems. Responsibilities include database architecture, configuration, backup and recovery, high availability, disaster recovery, performance tuning, security controls, automation, data loading, migrations, integrations, and technical guidance. The consultant collaborates with customers and cross-functional teams throughout implementation and communicates solutions to technical and non-technical stakeholders.

Design and implement secure, scalable geospatial database platforms for defense and intelligence operations. Responsibilities include database administration, performance tuning, backup and recovery, high availability, disaster recovery, access controls, compliance, automation, data integration, and technical guidance. The role also involves collaborating with customers and cross-functional teams throughout requirements, design, implementation, and deployment.

Designs, implements, secures, and optimizes scalable enterprise database and geospatial data platforms for mission-critical Defense and Intelligence systems. Responsibilities include database architecture, configuration, backup and recovery, high availability, disaster recovery, performance tuning, access controls, compliance, automation, data loading, migrations, integrations, and customer-facing technical guidance.

The Principal Automation Engineer will lead the design, delivery, and administration of data historian and integration platforms in pharmaceutical manufacturing, ensuring compliance with cGMP standards and successful project implementation.

Manage, design, and optimize data activities for federal IAM systems. Develop data models, file layouts, source-to-target mappings, data dictionaries, integrations, ETL processes, and analytics support for identity analysis and fraud detection. Administer and tune databases, including configuration, backups, monitoring, capacity planning, and performance optimization. Support secure handling of identity and PII data, network-related data flows, documentation, token management processes, and collaboration across development, security, and operations teams.

Build and maintain ELT pipelines, data models, semantic layers, and personalization signals for client retention and marketing tests. Partner with machine learning, product, marketing, design, and architecture teams to prepare predictive data, connect signals to CRM channels, support real-time event processing, and document a scalable data foundation. Use AI coding assistants daily to accelerate development, testing, and reviews in a fast-moving discovery environment.

Build and operate Helios’s acquisition and document-processing infrastructure, including web crawlers, connectors, fault-tolerant pipelines, multilingual document and media processing, OCR, extraction, transcription, and enrichment. Establish data contracts, provenance, versioning, observability, security, and correction propagation across distributed systems. Scale batch and real-time CPU/GPU workloads while supporting international sources and restricted environments.