Top Data Engineer Jobs in Portugal

Principal Engineer responsible for architecting scalable, secure, near-real-time data pipelines and modernizing legacy systems onto GCP. The role develops data models, APIs, microservices, automation, and CI/CD workflows; supports AI and advanced analytics integrations; and advances data governance, lineage, compliance, access control, and quality monitoring. The engineer partners with product, analytics, and engineering teams to deliver data solutions for digital, retail, and operational use cases.

Designs and maintains scalable data architecture, warehouses, ETL/ELT pipelines, and data platforms. Responsibilities include ensuring data quality, integrity, governance, accessibility, reliability, and performance; supporting customer onboarding and analytics tools; contributing to architecture and engineering best practices; troubleshooting complex data issues; and participating in on-call rotations. The role collaborates with engineering, product, solutions, business intelligence, and other cross-functional teams in healthcare and social care data environments.

Develop machine learning, statistical, graph-based, and data-mining algorithms for national-security missions. Build, optimize, and validate AI/ML and large language models; create feature vectors, experiments, simulations, visualizations, and predictive analytics; and implement prototypes in production frameworks. Collaborate with subject-matter experts to automate analysis, guide analytic development, and deliver data-driven insights. Experience with LLMs, RAG, agents, GPU computing, and active TS/SCI clearance with polygraph is required.

Builds and maintains production-grade ETL/ELT pipelines across legacy on-premise systems and AWS/Azure cloud platforms, centralizing data in Snowflake for analytics, machine learning, feature stores, and generative AI. Develops vectorization and embedding pipelines, optimizes Snowflake performance and cloud costs, manages cross-platform orchestration, and implements data quality and observability frameworks. Partners with IT, security, MLOps, data science, and infrastructure teams to deliver scalable, governed data solutions.

Design and build resilient data pipelines integrating files, APIs, services, databases, and mission sources. Develop extraction, normalization, enrichment, validation, cataloging, routing, ingestion, and event-driven workflows. Preserve geospatial metadata, provenance, lineage, security attributes, and data quality. Apply AI, RAG, MCP, and agentic capabilities to improve data discovery and access. Build Node.js applications and Oracle Database integrations while collaborating with engineering, cloud, security, AI, and mission teams.

Design and operate the data quality layer for a Databricks lakehouse using DQX. Translate legacy SQL validation logic into automated checks, quarantine invalid records, establish quality gates, integrate checks with batch and streaming pipelines, store results in Delta and Unity Catalog, build dashboards and alerts, and deploy version-controlled rules through CI/CD.

Designs and implements Databricks Unity Catalog access controls, security architecture, identity governance, data classification, and compliance automation. Leads RBAC and ABAC models, dynamic views, row- and column-level security, masking, service principal integration, and infrastructure-as-code deployments using Terraform or Databricks Asset Bundles. Establishes security guardrails, templates, tagging standards, and scalable workflows while partnering with data, platform, and workspace engineering teams.

Architect and manage cloud environments in classified regions using infrastructure-as-code and automation. Build and maintain ETL/ELT pipelines integrating security, vulnerability, event, and log data across ACAS, Elastic, and Splunk. Implement data quality, normalization, enrichment, governance, security, and compliance controls. Optimize ingestion and automate workflows, troubleshoot integrations, maintain schemas and documentation, and support dashboards and visualizations. Collaborate with cybersecurity teams to deliver scalable data solutions.

Build, deploy, and operationalize complex data pipelines and solutions using Databricks, cloud platforms, Python, and SQL. Responsibilities include data transformation, cleansing, governance, security, quality, source analysis, testing, defect resolution, and support for AI, machine learning, and business intelligence. The role also involves cross-team collaboration, stakeholder education, and delivery of resilient data products.

Leads hands-on design, development, and optimization of AI data movement and distributed storage systems. Responsibilities include integrating NVIDIA NIXL and DDN Infinia with GPU inference platforms, optimizing GPU-to-storage I/O using GPUDirect Storage, RDMA, and NVMe-over-Fabrics, developing KV cache and multi-tier storage strategies, benchmarking production systems, resolving performance bottlenecks, influencing distributed inference architecture, and mentoring engineers.

Interns will work with Data Solution Engineers to solve business problems and build data assets for actuarial and product management teams. They will receive training in Snowflake, SQL, Azure Data Factory, Azure Databricks, SAS, SQL Server, Python, and Power BI; collaborate with mentors; complete project tasks; and participate in community service. The role is fully in-office in West Bend or Madison, Wisconsin.

Designs and maintains the College’s enterprise data and AI platform. Develops integrations, governed data pipelines, warehouses, APIs, MCP services, dashboards, analytical applications, and AI-supported workflows. Establishes testing, monitoring, security, access controls, data governance, and evaluation standards. Partners with institutional offices to translate business needs into secure technical solutions while investigating unfamiliar systems, APIs, schemas, and workflows.

Own the enterprise product data architecture for Allegion’s Global Software Solutions business. Define unified data models, schemas, pipelines, APIs, catalogs, governance standards, and device telemetry architecture across multiple business units. Lead data onboarding, platform convergence, architecture audits, compliance, and engineering enablement. Partner with enterprise data, AI, identity, and product engineering teams to make governed product data usable for analytics and agentic AI.

Designs, builds, and operates scalable batch and streaming data pipelines, ELT/ETL workflows, and cloud data infrastructure. Ensures data reliability, quality, observability, lineage, performance, and cost efficiency across enterprise domains. Partners with analytics engineers, BI teams, and business stakeholders to deliver analytics-ready datasets. Establishes engineering practices including version control, CI/CD, automated testing, infrastructure-as-code, architecture standards, and documentation.

Architects, builds, and scales data pipelines, ETL processes, data models, and platforms using dbt, Snowflake, Airflow, and Fivetran. Leads data engineering best practices including CI/CD, data quality, governance, and observability. Collaborates with Data Science, Engineering, Product, and business stakeholders; mentors engineers and data scientists; contributes to architecture and technical decisions; and participates in on-call support.

Designs, builds, deploys, and supports scalable Databricks data pipelines and lakehouse solutions for observability, infrastructure, and security data. Develops PySpark and Structured Streaming workloads, establishes data quality and governance standards, optimizes performance, and improves reliability and operational excellence. Partners with security, infrastructure, observability, and platform engineering teams to onboard data sources, implement access controls, advance CI/CD practices, and deliver trusted enterprise data products.

Designs, builds, and maintains scalable Azure data pipelines and ELT frameworks using Databricks, SQL, Python, and PySpark. Implements Azure DevOps CI/CD, monitoring, security, infrastructure automation, and production support. Collaborates with BI teams on Power BI datasets, documents data solutions, participates in Agile delivery, and mentors junior engineers. The role requires strong data modeling, structured and semi-structured data expertise, performance tuning, and data governance awareness.

Build and optimize enterprise-scale Snowflake data solutions, including ingestion, ETL pipelines, transformation, quality assurance, production deployment, legacy warehouse migration, and workflow automation. Establish data governance, compliance policies, and data quality rules while supporting cloud-based architectures and efficient data consumption.

Designs scalable Databricks solutions and ETL/ELT pipelines while administering MariaDB and SQL Server environments. Responsibilities include database design, performance tuning, backup and disaster recovery, security and access management, data modeling, quality and lineage, and troubleshooting complex data issues. The role collaborates with stakeholders and technical teams, translates requirements into secure solutions, provides technical direction, and delivers demonstrations and training for Department of Transportation support.

Develops, tests, documents, operates, and troubleshoots application and medical-device interfaces using Epic Bridges, HL7, X12, DICOM, FHIR, and interface engines. Translates business requirements into technical specifications, supports FHIR adoption, manages small-to-medium integration projects, maintains compliance and architecture artifacts, develops testing strategies, mentors junior staff, and provides technical support. The role also includes documentation, technology trend briefings, on-call support, and protection of patient health information.

Supports secure data pipelines, ETL/ELT workflows, data transformations, and analytics-ready datasets in a classified DoD environment. Collaborates with data scientists, engineers, and mission stakeholders while using Python, SQL, Spark, Databricks, and comparable platforms. Performs data validation, modeling, quality practices, testing, documentation, and Agile development. The role is fully on-site in a SCIF at Camp Smith, Hawaii, and requires an active Top Secret/SCI clearance before starting.

Designs, builds, deploys, and maintains scalable data platforms, warehouses, lakes, ETL/ELT pipelines, and batch or streaming workflows. Optimizes cloud data lake and pipeline performance, manages data governance and lifecycle solutions, and collaborates with multidisciplinary agile teams. The role supports mission-driven client projects involving disparate structured, unstructured, and event-streaming data.

Design, build, and deploy agentic AI solutions (Google Gemini, Claude, ADK); maintain BigQuery data warehouse and ETL pipelines; troubleshoot tracking across Google Analytics, Omeda, Piano, and Salesforce; create dashboards and monitoring to ensure data quality and measure agentic impact across Sales, Marketing, Editorial, and Finance.

Lead design, build, and operate scalable Databricks/Delta Lake data pipelines and Kimball dimensional models using dbt. Manage governance with Unity Catalog, optimize performance and cost, operationalize ML with MLflow, and coordinate/quality-check offshore vendor engineering. Mentor engineers, uphold standards, and deliver trusted data products that power analytics, reporting, and MLOps workflows.

Lead the technical design and operation of consumer-facing data products on a Databricks lakehouse. Own medallion architecture, dimensional modeling, ODCS data contracts, data quality, observability, CI/CD, incident response, and production standards. Write and review Python and SQL, guide code reviews, mentor engineers, collaborate with product, platform, governance, and ML teams, and ensure compliant, reliable delivery in a regulated insurance environment.