Top Data Engineer Jobs in Portugal

Leads data platform domains, sets technical direction and roadmaps, manages data engineers, and owns ingestion, orchestration, dbt transformations, data quality, monitoring, access controls, and client data feeds. The role includes incident response, vendor and budget decisions, HIPAA-compliant data governance, entity resolution, stakeholder communication, and approximately 65% hands-on engineering work.

Analyze and validate In-Line Inspection (ILI) data to support pipeline integrity programs under 49 CFR Parts 192/195. Collaborate with vendors, update databases, identify data inconsistencies and trends, support dig list development, and provide ad hoc engineering analyses. Hybrid role based in Tulsa with no extensive travel required.

Designs, develops, and optimizes scalable data pipelines, architectures, and cloud-based data solutions using Azure services and Databricks. Translates business requirements into reliable data systems, supports data security, privacy, quality, and governance, and provides technical expertise during incidents. The role oversees testing, drives continuous improvement and engineering standards, participates in infrastructure planning, and mentors less experienced data engineers.

Designs and operates scalable streaming and batch data pipelines using Azure Data Explorer, Kafka, Cribl, and Azure Data Factory. Develops data models, warehouses, governance, security controls, curated datasets, and analytics dashboards in Power BI and Tableau. Partners with technical and business stakeholders to deliver data solutions, optimize analytical workloads, ensure data quality, and support decision-making. Mentors data engineers and contributes to architecture, data security, and emerging technology adoption.

Design, develop, and maintain Customer Data Platform solutions and data pipelines to create unified customer profiles, manage identity resolution, enable audience segmentation and activation, ensure data quality and governance, and support integrations with marketing, CRM, and cloud data systems.

Leads end-to-end data engineering and analytics platform development, including Power BI dashboards, semantic models, cloud data pipelines, governance, quality monitoring, CI/CD, and legacy workload modernization. Partners with stakeholders to define scalable solutions, validates KPIs, troubleshoots production issues, establishes engineering standards, and mentors team members.

Provides Level 3 production support for enterprise mainframe and distributed data platforms. Troubleshoots complex issues, performs root cause analysis, validates data integrity, and supports COBOL, JCL, DB2, Oracle, SQL, APIs, batch processing, and backend services. Partners with development, infrastructure, and database teams to maintain reliable business-critical systems.

Designs heat rejection and HVAC systems for mission-critical data centers, including cooling selection, CFD analysis, heat-load calculations, redundancy, fault tolerance, energy efficiency, air quality, and capacity planning. Coordinates mechanical systems with electrical, UPS, emergency power, fire suppression, and other infrastructure. The role is client-facing, primarily remote, and requires occasional travel, a professional engineering registration, and significant data center experience.

Designs and optimizes mechanical systems for mission-critical data centers, including HVAC, heat rejection, cooling distribution, airflow, redundancy, fault tolerance, heat-load calculations, CFD analysis, energy efficiency, air quality, and capacity planning. Coordinates mechanical designs with electrical and other engineering disciplines, supports client-facing projects, and ensures compliance with data center standards and best practices.

Designs and optimizes mechanical systems for mission-critical data centers, including HVAC, heat rejection, cooling, airflow, redundancy, fault tolerance, heat-load calculations, capacity planning, air quality, and energy efficiency. Performs and directs CFD analyses, coordinates with electrical and other engineering disciplines, supports client-facing projects, and ensures compliance with data center standards and best practices.

The Data Engineer Intern supports data transformation, warehouse concepts, pipeline development, documentation, and migration processes across development, UAT, and production environments. The role involves learning coding, debugging, data modeling, ETL/ELT, and technical best practices through mentorship, project assignments, code reviews, and cross-functional collaboration. This is a 10–12 week, in-person internship in Des Moines, Iowa.

Designs and automates software testing for business intelligence, data warehouse, reporting, and ETL projects. Develops SQL and Python validation routines, tests Snowflake and Microsoft SQL Server data, verifies SSRS, Tableau, and Sigma reports, and enhances Talend ETL test frameworks. Documents results, resolves data discrepancies with stakeholders, participates in Agile ceremonies, and mentors junior engineers.

Analyzes wafer fabrication, equipment, sensor, metrology, and manufacturing data using AI, machine learning, statistics, and data-mining techniques. Develops data pipelines, analytical tools, dashboards, deployed models, and monitoring methods for anomaly detection, yield prediction, excursion analysis, and root-cause investigation. Collaborates with engineering, manufacturing, MES, and AI/ML teams to translate results into actionable insights, support experiments, improve processes, and establish responsible AI and data-quality practices.

Designs, optimizes, and leads complex data pipelines, integrations, warehousing solutions, and enterprise data platforms. Partners with analytics and data science teams, drives automation and infrastructure scalability, evaluates emerging technologies, leads technical discovery, and develops data governance policies. Requires advanced programming and SQL expertise, big data and cloud experience, large-scale data warehousing knowledge, and strong analytical problem-solving skills.

Supports the IBCS program as a Link 16 liaison and Tactical Data Link Engineer. Troubleshoots multi-system technical issues, assesses communications and Multi-TDL architectures, supports corrective actions, and collaborates with software development and integration teams. The role integrates and configures virtual machines, performs software updates, tracks work in JIRA and Confluence, and maintains technical documentation. Candidates need substantial military and DoD C4ISR experience, command-and-control systems expertise, Security+ certification, U.S. citizenship, and clearance eligibility.

Leads enterprise data engineering for NASIC, designing data structures, pipelines, standards, automation, and architecture. Advises senior leadership on data engineering and analytics, guides cross-functional personnel, defines business requirements, and manages projects from inception through implementation. Requires expertise in Tableau, SharePoint, business analytics, Python, SQL, ETL, Power BI, and data preparation, along with a current Top Secret clearance with SCI adjudication and U.S. citizenship.

Design, build, and operate ingestion pipelines and normalized security data products for vulnerability risk management. Transform raw evidence into model-ready features, enable ownership routing and remediation workflows, and maintain data quality, lineage, and observability. Partner with security, engineering, and platform teams to support reporting, risk models, and shift-left scanning readiness.

Manage Oracle and PostgreSQL databases across on-premises and AWS environments, including upgrades, migrations, performance tuning, security, and backup recovery. Design and maintain ETL pipelines using Talend, SQL, Power Automate, and related tools. Perform data profiling, quality analysis, governance, and cloud migration activities. Create technical architecture and lineage documentation while supporting regulated, audit-ready data platforms and integrations.

Implement and maintain Immuta and Unity Catalog access-control policies, translating approved governance requirements into technical rules and configurations. Develop and execute tests for filtering, masking, entitlements, and policy behavior; troubleshoot authorization and platform issues; document controls, dependencies, evidence, and operational procedures. Collaborate with cloud operations, data engineering, security, IAM, privacy, governance, and business stakeholders while contributing reusable policy-engineering patterns and integration architecture.

Own and evolve Later’s data platform across ingestion, orchestration, storage, transformation, and consumption. Build reliable batch and real-time pipelines, backend services, APIs, infrastructure as code, CI/CD automation, observability, data quality controls, and secure GCP-AWS data movement. Modernize BigQuery and lakehouse infrastructure, improve performance and cost, mentor engineers, and establish governance, metadata, lineage, and freshness foundations for analytics, machine learning, LLMs, and AI agents.

Leads enterprise data platform, master data management, semantic layer, governance, quality, and modeling initiatives. Partners with executive and client data leadership while remaining hands-on with architecture and delivery. Requires production ownership of MDM programs, large-scale platform builds, semantic layers, and complex acquisition-driven data environments. Provides deep technical expertise in Snowflake, cloud platforms, governance, data quality, dbt, orchestration, streaming, and batch pipelines, while driving modernization and organizational alignment.

Leads electrical systems and Command & Data Handling subsystem engineering for spacecraft. Responsibilities include requirements decomposition, electrical architecture, interface and connectivity design, verification planning, avionics integration and testing, telemetry and command implementation, supplier technical oversight, risk mitigation, and flight hardware development. The role coordinates multidisciplinary teams, manages technical execution, budgets, schedules, and customer relationships, and supports hardware delivery throughout the development lifecycle.

Build and operate the Safeguards data platform: ingestion and processing pipelines, data stores, governance, retention and access controls, and portable systems across cloud providers. Maintain high operational standards, ensure data integrity and privacy, and partner with analysts, investigators, and researchers to provide tooling and reliable data for detection, review, and mitigation systems.

Develop and optimize multilingual machine translation and speech models for low-resource languages. Build and manage multilingual datasets, scalable data pipelines, and end-to-end MLOps workflows. Deploy cloud-native machine learning solutions on AWS using containerized environments and CI/CD practices. Conduct model testing, benchmarking, monitoring, troubleshooting, and lifecycle management while researching emerging NLP, speech, generative AI, and machine learning technologies.

Designs and operates scalable data pipelines and platforms for analytics, machine learning, and Agentic AI. Develops production-grade Python and SQL solutions, implements data quality and monitoring, supports end-to-end ETL/ELT workflows, and partners with data scientists, analysts, and business stakeholders. The role also includes code reviews, testing, source control, production support, mentoring, and establishing engineering best practices. Familiarity with Celonis, SAP, and Salesforce is preferred.