Top Data Engineer Jobs in Portugal

Designs, builds, and optimizes scalable data pipelines, warehouses, lakes, and ingestion platforms using Kafka, Elastic Stack, AWS, and Kubernetes. Integrates disparate network operations data while ensuring quality, security, and DoD compliance. Automates ETL/ELT, validation, monitoring, CI/CD, and deployment processes, supports dashboards and analytics, troubleshoots platform performance, and documents architecture and operational procedures.

Designs, builds, and maintains scalable data pipelines, warehouses, lakes, and integrations using Kafka, Elastic Stack, AWS, and Kubernetes. Optimizes ingestion, querying, indexing, storage, and platform performance while supporting visualization, CI/CD, automation, security, and DoD/DISA compliance. Collaborates across engineering, analytics, software, and network operations teams, documents architectures and procedures, and resolves data-platform issues in classified enterprise environments.

Builds and maintains scalable data pipelines, warehouses, and lakes for analytics and reporting. Integrates network operations data using Kafka, Elastic Stack, AWS, and OpenShift/Kubernetes; develops ETL/ELT automation, dashboards, CI/CD processes, and data validation workflows. Optimizes ingestion, queries, indexing, storage, and cluster performance while ensuring security and DoD/DISA compliance. Troubleshoots platform issues, collaborates with analysts and visualization engineers, and documents architectures and operational procedures.

Leads and mentors the Data Engineering team while remaining hands-on in designing, building, and maintaining scalable data pipelines, warehouses, integrations, and infrastructure. Establishes architecture, reliability, quality, and performance standards; guides technical delivery; and resolves complex issues. Partners with Finance and business stakeholders to translate data needs into practical solutions, sets technical direction, evaluates technologies, and communicates strategy, risks, and recommendations to leadership.

Develops and maintains data architectures, databases, data warehouses, ETL pipelines, migrations, stored procedures, replication, and data governance processes. Collaborates with analytics teams and business stakeholders to define requirements and enable business intelligence, reporting, and predictive modeling. Maintains data infrastructure across Azure and on-premises environments while improving performance, reliability, quality, and CI/CD practices.

Designs, develops, and maintains enterprise-scale Apache NiFi data flows for secure data onboarding, integration, transformation, and governance. Develops custom Java processors, controller services, APIs, and validation components; integrates databases, APIs, messaging systems, Kafka, and cloud storage. Optimizes clustered pipelines, implements metadata and security controls, supports Zero Trust requirements, troubleshoots complex data movement issues, and mentors engineers while contributing to architecture, standards, and documentation.

Designs, develops, and maintains enterprise Apache NiFi data flows and custom Java processors for secure, scalable data integration. Responsibilities include building ingestion pipelines, integrating APIs, databases, message queues, Kafka, and cloud storage, managing metadata and governance, optimizing clustered deployments, and implementing Zero Trust security controls. The role supports complex data onboarding, transformation, validation, workflow automation, and enterprise architecture initiatives.

Build and operate Lakehouse data pipelines, product features, machine learning and generative AI components, testing, monitoring, instrumentation, and documentation. Collaborate with product managers, engineers, and business users to clarify requirements, deliver production solutions, investigate defects, and improve reliability and performance. Participate in code reviews, technical design discussions, and backlog-driven development while following engineering standards and contributing to scalable Data & AI products.

Leads and delivers complex data engineering projects, designing scalable data infrastructure, pipelines, warehouses, and data quality solutions. Recommends tools and architectures, optimizes data movement and performance, collaborates across technical teams, mentors engineers, and translates technical concepts for clients and nontechnical stakeholders. The role may also involve real-time processing, data modeling, transformation, security, and MLOps.

Design, develop, test, and maintain ETL solutions and data warehouse structures using SSIS and SQL Server. Build and support SSAS models, optimize ETL performance, ensure data quality, partner with stakeholders, and produce technical documentation to support BI and reporting initiatives.

Designs, builds, and maintains scalable ETL, batch, and streaming data pipelines using Airflow, Kafka, Python, AWS S3, Trino, OpenSearch, and related technologies. Develops data APIs, optimizes storage and retrieval, supports data governance, and integrates classified data securely. Collaborates with software developers, analysts, and product teams to deliver reliable data solutions for production applications. This hybrid Fort Bragg role requires active TS/SCI clearance, CI Poly eligibility, and U.S. citizenship.

Build and operate AWS GovCloud data infrastructure across development, preproduction, and production environments. Establish PostgreSQL platforms, infrastructure-as-code with Chef, BI infrastructure, identity integrations, monitoring, observability, CI/CD, and disaster recovery. Support data pipelines, troubleshoot incidents, optimize databases, and ensure FedRAMP and FISMA compliance. Collaborate with security, compliance, DevOps, and data engineering teams while delivering greenfield infrastructure from architecture through production.

Supports cybersecurity engineering for avionics and government systems by assessing risks, developing requirements and controls, designing security architectures, applying NIST controls and STIGs, and supporting certification efforts. The role requires systems thinking, Linux and scripting experience, Cross Domain Solution knowledge, and eligibility for a security clearance. Desired qualifications include C, C++, Java, and Python experience, RMF familiarity, and willingness to travel up to 10%.

As a Data Engineer at OneImaging, you'll design and maintain scalable data pipelines and infrastructure, collaborate on analytics, and ensure compliance with healthcare regulations.

Develop and maintain data cleaning, preprocessing, integration, and quality checks. Build dashboards and complex visualizations (Tableau or Power BI). Apply AI/ML techniques for unstructured data analysis, provide data-driven analysis, and perform quality assurance to support government/intelligence decision-making.

Leads the design, engineering, and commissioning of high-voltage electrical infrastructure for hyperscale data centers. Responsibilities include substation and power distribution design, utility interconnection, electrical system studies, redundant power architectures, generation and energy storage integration, technical leadership, design reviews, construction support, and client advisory work.

Develop and manage scalable ETL/ELT pipelines and data warehouses, ensuring performance, reliability, integrity, and consistency. Monitor systems, troubleshoot issues, collaborate with technical and business teams, document architectures, and improve data infrastructure for scalability. The role requires production-quality Python, AWS experience, strong debugging skills, and approximately four years of fintech or startup experience. It is based in Palo Alto with three days per week in the office.

Designs, builds, and maintains scalable Databricks and PySpark data pipelines; develops Python and SQL transformations; identifies insights from ambiguous datasets; and ensures data quality, governance, documentation, and reliable delivery. Collaborates with stakeholders and cross-functional teams to integrate data into applications and dashboards, troubleshoot pipeline issues, and support a Department of Defense Navy client.

Develop and operationalize data applications using Palantir Foundry for national security clients. Translate stakeholder needs into technical solutions, ingest and transform data, build workflows and applications, support scalable data platforms, and lead analytics projects. The role also involves advising clients on data-driven mission impacts, collaborating with Agile teams, and applying DevSecOps, AI/ML integration, security, and compliance practices.

Build and operationalize data pipelines and solutions supporting AI, machine learning, and business intelligence. Responsibilities include designing data solutions, analyzing and cleansing data, implementing governance and security practices, testing transformations, resolving defects, and collaborating across teams. The role requires Python, SQL, AWS, Databricks, Terraform, API design, and AI platform experience.

Builds and maintains scalable batch and streaming data pipelines supporting analytics, machine learning, and business operations. Responsibilities include writing Python, SQL, and Spark code; ensuring data quality and reliability; monitoring and troubleshooting pipelines; implementing testing and observability practices; documenting data architecture; and collaborating with analysts, data scientists, product managers, and engineering teams in an agile environment.

Build and own Dexory’s company-wide data foundation, integrating operational, product, commercial, contractual, and telemetry data. Define trusted data models, business metrics, SLAs, and KPIs; establish secure queryable datasets and AI-assisted natural-language access. Own pipeline health, data quality, architecture, and build-versus-buy decisions while partnering with engineering teams. As the founding data hire, set standards, deliver early value, and help recruit and lead the future data function.

Build and maintain data pipelines in Azure Synapse using Spark, Python, SQL, and C#. Apply data warehouse and lakehouse modeling standards, collaborate with analysts and testing teams, troubleshoot data issues, and develop machine learning and regression analysis capabilities using Azure ML and related tools.

Build and operate Pivotal’s flight data warehouse and telemetry pipelines using AWS Glue, Athena, SQL, and Python. Design curated data marts, fleet health alerting services, data quality gates, dashboards, and query interfaces. Own data infrastructure, deployment, monitoring, and schema evolution end to end while collaborating with firmware, GNC, battery, flight operations, systems engineering, and MRO teams on telemetry and airworthiness decisions.

Build and operate core data infrastructure for edge and hybrid environments, including ingestion, OT/IoT integrations, real-time streaming, data contracts, schemas, validation, lineage, observability, telemetry, and scalable query access. The role requires production ownership, reliability practices, customer integration, and collaboration across engineering and customer-facing teams. Candidates should have 6+ years of experience with production data, streaming, or integration systems and proficiency in Python and/or Go.