Top Data Engineer Jobs in Portugal

Designs and maintains scalable data architectures, ETL workflows, batch and real-time pipelines, and SQL/NoSQL storage solutions supporting intelligence operations. Ensures data quality, governance, security, lineage, and compliance with IC and DoD standards. Collaborates with analysts and technical teams to deliver reliable intelligence data and participates in mission-planning and coordination forums.

Supports AI and cloud solution development by extracting, transforming, standardizing, and integrating text, JSON, geospatial, and other datasets. Assists with automated data ingestion, data services, pipelines, and machine learning algorithm integration for testing and operational deployment. Coordinates data requirements with project managers, customers, vendors, software engineers, architects, and data teams while managing changing priorities in a national security environment.

Supports the development and maintenance of data ingestion, transformation, and integration pipelines across enterprise systems. Writes and optimizes SQL, assists with database management, supports BI reporting, monitors data quality and system performance, troubleshoots issues, documents data flows, and gathers requirements for automation. Works under senior engineering guidance while developing skills in cloud platforms, ETL/ELT, data modeling, governance, MuleSoft, and Azure Data Factory.

Designs, develops, and optimizes scalable Azure-based data engineering solutions, including lakehouses, warehouses, ETL/ELT pipelines, Databricks notebooks, and analytics workflows. The role supports enterprise reporting, AI and machine learning initiatives, feature engineering, Generative AI, and MLOps. Responsibilities include performance tuning, CI/CD automation, production support, technical design, lifecycle management, stakeholder collaboration, and translating business requirements into secure, reliable data platforms.

Build, deploy, and operationalize data pipelines and solutions supporting AI, machine learning, and business intelligence. Responsibilities include data transformation, cleansing, governance, security, quality management, source analysis, testing, incident resolution, and defect remediation. The role collaborates across teams, supports data products, educates users, and applies software engineering and DevOps practices to deliver reliable analytical data solutions.

Leads a data engineering team and sets the strategic direction for scalable, secure data initiatives. Oversees project planning, resource allocation, engineering standards, documentation, technical debt, and complex issue resolution. Partners with business leaders, data scientists, and IT teams to translate organizational needs into technical solutions. Requires expertise in AWS, cloud data platforms, data modeling, governance, orchestration, real-time processing, programming, and enterprise data management.

Develop, maintain, and enhance software systems supporting AI-driven automation and efficiency. Design, develop, and deploy scalable AI/ML models and tools, including prompt engineering and retrieval-augmented generation solutions. Collaborate with stakeholders to translate mission requirements into technical solutions and analyze data structures and objects in support of a classified Intelligence Community customer.

Designs, deploys, and maintains enterprise telemetry ingestion pipelines and data onboarding processes. Configures Splunk forwarders and edge processors, develops tagging and field-extraction schemas mapped to CIM, creates technology add-ons, and troubleshoots parsing and timestamping issues. The role also implements secure data transport, edge filtering, data reduction, storage optimization, and routing across mission platforms while maintaining documentation and supporting threat hunting and compliance reporting.

Develop, maintain, test, and enhance complex software systems for an enterprise engineering contract within the Intelligence Community. Design software solutions, analyze system performance and workflows, investigate issues, and evaluate COTS/GOTS alternatives. Support cloud infrastructure using OpenStack and comparable platforms, with Linux, Python, network automation, cloud security, and IT operations responsibilities. The role is performed onsite at a customer location and requires an active TS/SCI clearance with polygraph.

Designs, develops, tests, maintains, and optimizes data pipelines and software systems using SQL, Python, and Apache Airflow. Supports technical projects, documents systems, troubleshoots application performance, evaluates user requirements, and develops technical specifications. Collaborates with epidemiologists, statisticians, and researchers, while mentoring staff and translating academic research needs into software solutions.

The Data Engineer will develop and document research data products, contribute to scientific papers and findings, lead research efforts, coordinate with academic partners, and propose independent research goals. The role also includes project management, technical documentation, meetings, and collaboration with statistical developers, data engineers, and researchers. Experience with Apache Airflow, SQL, data visualization, web development, statistics, analytics, and agile software development is desired.

Build and operate production-grade AML data products, ETL pipelines, data models, integrations, and ML-ready datasets. Ensure data quality, lineage, security, governance, observability, reliability, and regulatory compliance. Support transaction monitoring, customer segmentation, risk rating, sanctions screening, and financial crime prevention initiatives. Lead architecture decisions, production support, incident response, CI/CD improvements, automated testing, code reviews, mentoring, and engineering standards.

Designs and maintains ELT pipelines, warehouse integrations, data models, and data quality processes. Collaborates with data scientists, analysts, engineers, and stakeholders to deliver scalable analytical solutions. Responsibilities include data integration, governance, security, performance optimization, exploratory analysis, visualization, and cloud-based API ingestion. Requires strong SQL, DBT, Snowflake, Azure Data Factory, cloud, and scripting experience, plus leadership and communication skills.

Design, implement, and optimize large-scale data ingestion, cleansing, transformation, loading, replication, and display systems. Develop data pipelines, profiling, deduplication, matching logic, and custom data-source solutions. Maintain data-layer documentation, collaborate with data scientists on AI/ML workflows, and use Java technologies, REST APIs, Airflow, ETL, SQL, and Linux in a Big Data environment.

Designs, deploys, and maintains Bastille WIDS sensor arrays across global data center facilities. Integrates wireless threat telemetry with Genetec Security Center, tunes RF monitoring, performs site surveys, develops coverage plans and technical documentation, establishes alerting workflows, maintains wireless device inventories, and investigates detection failures. Collaborates with network, IT security, SOC, vendors, and infrastructure teams while providing up to 20% international travel and after-hours support.

The Forward Deployed Data Engineer will manage AI-automated data platform migration projects, ensuring timely delivery and communication with clients while utilizing proprietary tools.

Designs and maintains scalable data pipelines, data quality frameworks, and cloud-native data solutions using Spark, Databricks, Hadoop, AWS, and advanced SQL. Implements validation, monitoring, observability, and automated remediation capabilities. Applies AI/ML, anomaly detection, and statistical modeling to improve data quality. Provides production support, resolves complex incidents, contributes to architecture and engineering standards, and collaborates with cross-functional data and engineering teams.

Paid, full-time electrical engineering intern supporting data center critical infrastructure. Responsibilities include equipment rack mounting, fiber and CAT6 cabling, HVAC and power system monitoring, infrastructure impact assessments, bill of materials development, and creating statements of work and technical designs using Visio, PDF, and PowerPoint. The internship also includes mentorship, professional development, networking, and cross-functional activities.

Designs, implements, and manages Azure cloud data platform infrastructure, including Azure Data Factory, ADLS Gen2, Logic Apps, Blob Storage, Snowflake, and Databricks. Develops GitHub Actions CI/CD pipelines and Terraform infrastructure-as-code solutions. Collaborates with cross-functional teams, monitors platform performance, troubleshoots issues, applies security best practices, and delivers scalable, reliable data solutions.

Design, build, and maintain batch and streaming data pipelines; ingest, transform, and optimize data for analytics and BI; ensure data quality, reliability, and performance; implement monitoring/alerting; support MLOps and analytics workloads; collaborate with data scientists and BI teams; document AI systems and RAG/Cortex-based solutions.

Develops and maintains secure data pipelines, ETL/ELT workflows, data transformations, and analytics-ready datasets. Processes structured and unstructured data using platforms such as Databricks, Spark, Palantir Foundry, and Maven Smart Systems. Collaborates with data scientists, engineers, and mission stakeholders while applying data validation, modeling, quality, testing, documentation, and Agile practices. The role requires onsite work in a SCIF and support for classified national security missions.

Own and build JSSI’s AI-first data platform, including Bronze, Silver, and Gold pipelines in Microsoft Fabric and OneLake. Develop governed semantic layers for Power BI, ingest data into Azure SQL and ADLS Gen2, and enforce quality, lineage, security, governance, and PII controls aligned with Entra ID. Expose curated datasets to AI agents through approved APIs or MCP servers while using Claude Code and documentation-first engineering practices.

Build and maintain data pipelines and integrations across engineering, manufacturing, procurement, ERP, PLM, and business systems. Develop monitoring, dashboards, automation, and data governance practices that improve operational decision-making. Collaborate with cross-functional teams to translate requirements into durable tools, document system ownership and lineage, and support evolving organizational needs. This is a full-time, onsite role in Denver, Colorado.

Build, optimize, and maintain scalable data pipelines and reusable datasets for business intelligence, marketing, and data science. Develop federated data validation frameworks, optimize queries and data models, and protect user privacy and security. The role uses Python, SQL, AWS, Airflow, PostgreSQL, Iceberg, Snowflake, Spark, and other modern data-stack technologies. It is based in New York City with in-office work three days per week.

Own Double E’s data lake and improve data integrity by building ETL pipelines, data models, integrations, and reporting solutions. Manage Azure SQL and Power BI, consolidate ERP and CRM data across global offices, establish governance and documentation standards, and translate business needs into reliable, scalable data infrastructure. The role partners with technical and business stakeholders and supports modernization, system connectivity, and analytics initiatives.