Top Data Engineer Jobs in Portugal

Designs and leads data architecture, models, metadata standards, integration strategies, storage solutions, and virtualized data pipelines. Partners with business stakeholders, technical teams, and product owners to define data requirements and digital ecosystem recommendations. Supports data governance, quality, security, visualization, and analytical systems while guiding technology assessments and digital transformation initiatives.

Design and build production AI, data analytics, and cloud solutions for product engineering. Own end-to-end architecture, agentic systems, evaluation standards, data pipelines, AWS platforms, APIs, and user interfaces. Develop full-stack applications, establish technical standards, mentor engineers, manage developers, and partner with engineering teams to move prototypes into adopted production systems. The role requires hands-on Python, SQL, modern front-end, LLM orchestration, RAG, data engineering, cloud, and cost-aware architecture expertise.

Designs and leads spacecraft data architectures for Blue Ring satellites, including command and telemetry databases, parameter data, onboard storage, uplink and downlink flows, and data prioritization. Collaborates with flight software, spacecraft engineering, operations, systems engineering, and test teams to implement, automate, verify, and scale data solutions across missions. Requires extensive spacecraft development and operations experience, programming expertise, and knowledge of CCSDS standards and command sequencing.

Designs and maintains scalable data pipelines, warehouse models, and analytics solutions. Builds natural-language data interfaces using GenAI and LLM techniques, optimizes SQL, improves data quality and observability, and supports distributed data platforms on AWS or GCP. Partners with engineering, analytics, business, and product teams, contributes to shared codebases, establishes development standards, and participates in production on-call and incident response.

Manage and enhance Splunk infrastructure, including data onboarding, ingestion pipelines, dashboards, queries, alerts, user management, retention, and performance troubleshooting. Integrate diverse data sources, normalize and route security data, support security operations, collaborate with stakeholders, and provide user training. The role requires Splunk architecture expertise, Linux and Windows administration, data pipeline development, and an active TS/SCI clearance with potential polygraph requirements.

Build and operate production data pipelines and enterprise data services supporting AI models, agents, and mission applications. Integrate structured and unstructured data across relational, document, vector, and graph systems; establish data quality, lineage, metadata, governance, and secure access practices; and collaborate with AI, platform, government, and commercial engineering teams. Deploy services in Kubernetes and classified environments while developing reusable ingestion, orchestration, documentation, and operational patterns.

Build and operate production data integrations and ETL pipelines using AWS Glue, PySpark, Python, SQL, and ClickHouse. Responsibilities include designing schemas, integrating unfamiliar data sources, monitoring pipeline health, debugging incidents, improving observability, supporting restricted-environment deployments, and participating in on-call operations. The role collaborates with forward-deployed engineers and requires full-time onsite work in New York City, occasional travel to Arlington, and eligibility for a U.S. government security clearance.

Analyzes and resolves vehicle commissioning, software validation, and diagnostic issues in a production environment. Responsibilities include testing software and vehicle functions, analyzing CAN logs and ECU data, tracking defects, developing fault-finding processes, creating dashboards and reports, troubleshooting data loggers, and collaborating with validation, production, and after-sales teams. The role also supports scalable validation data systems and process optimization.

Own business metadata and data governance activities across Finance, Commercial, HR, and Marketing. Partner with data stewards and domain owners to define, certify, map, validate, and publish business terms, metrics, KPIs, and data assets in Unity Catalog. Facilitate definition workshops, resolve terminology conflicts, improve Excel and Python intake processes, establish governance workflows, and document metadata lifecycle procedures.

Build and evolve scalable AWS data platforms, enterprise data warehouses, pipelines, models, and integrations. Develop Redshift schemas, implement data quality and observability controls, optimize data jobs, and support lineage and documentation. Partner with data science, analytics, and business teams to deliver reliable datasets. Participate in Agile ceremonies, code reviews, automation, and mentoring while promoting modern, reusable data engineering practices.

Own end-to-end infrastructure for large-scale AI training and inference, including GPU cluster orchestration, preprocessing pipelines, storage and network I/O, production inference optimization, multi-cloud deployments, infrastructure as code, and reliability. The role requires continued hands-on coding and technical ownership of substantial systems using Kubernetes, Python, Go, Terraform, and performance-oriented languages.

Secure cloud infrastructure, Kubernetes, containers, data pipelines, identity systems, secrets, CI/CD workflows, and software supply chains. Implement Terraform guardrails, encryption, network segmentation, IAM controls, observability, threat modeling, incident response, red-team exercises, tabletop drills, penetration testing, and compliance controls for creator and AI training data.

Build and operate highly available, reliable, and scalable distributed data services for Slack. Responsibilities include developing critical infrastructure such as edge caches, enterprise key management, data residency, image proxying, and shared-channel services. The role requires deep distributed-systems expertise, production infrastructure ownership, debugging complex architectures, and making sound engineering and product trade-offs. Services process millions of events per second and use Go, Java, and related cloud-native technologies.

Design, build, and maintain large-scale, fault-tolerant cloud data protection services for SaaS applications. Develop backup and recovery systems, APIs, administrative UIs, monitoring, automation, and build infrastructure. Troubleshoot scalability, stability, and critical production issues; collaborate with product and customer-facing teams; lead projects, conduct code reviews, and mentor junior engineers.

Develop robotics datasets and evaluations for embodied AI systems. Responsibilities include defining data schemas, annotations, quality standards, collection protocols, validation tools, and review workflows. The role also involves running experiments to assess how data quality and structure affect model performance, collaborating with research, engineering, vendors, and customers, and taking research tools from conception through deployment.

Design, build, test, and scale Gusto’s payments infrastructure and platform. Make architectural decisions focused on fault tolerance, scalability, and modularity; modernize Ruby/Rails and TypeScript/React systems; collaborate across engineering, product, design, data science, and operations; deliver software supporting millions of businesses; and mentor fellow engineers.

Leads the end-to-end architecture, deployment, operation, and scaling of AI compute infrastructure for orbital data centers. Owns GPU/CPU, networking, storage, orchestration, cloud-platform, spacecraft network, testing, and qualification strategies. Builds and manages the compute payload engineering organization, leads hardware/software co-design, and makes supplier, component, technology-partner, and make-or-buy decisions. Requires extensive hyperscale, HPC, AI infrastructure, GPU cluster, hardware, networking, storage, and team leadership experience.

Owns end-to-end spacecraft design and development for orbital data centers, including power, thermal, compute, communications, structures, and mechanisms. Leads complex CREO modeling, trade studies, structural and thermal analysis, tolerance analysis, and hardware verification and validation. Provides technical leadership to multidisciplinary engineers while remaining hands-on, collaborating with manufacturing and electrical engineering teams, and presenting design recommendations to program leadership.

Own and refine financial and profitability metrics, build curated data models, dashboards, and analytical views, and analyze large-scale financial data. Partner with Finance, Product, Operations, and Data teams to support planning, capital allocation, KPI development, reconciliation, and data quality. Design GenAI-powered self-service analytics tools and communicate insights, assumptions, and recommendations to technical and senior business stakeholders.

Manage the health, performance, reliability, and cost of customer Snowflake and Databricks environments. Responsibilities include customer onboarding, account and warehouse setup, permissions, data ingestion, query optimization, cost reporting, incident response, escalation support, and automation using Python and Terraform. The role also advises customers and internal teams on data platform best practices and participates in on-call rotations.

Lead the roadmap, delivery, evaluation, validation, upgrades, and lifecycle maintenance of digital manufacturing data systems, including historians, dashboards, reporting applications, and analytics platforms. Develop software enhancements, troubleshoot root causes, assess system risks, support regulated manufacturing operations, train users, collaborate with global stakeholders, and mentor engineers. The role requires expertise in manufacturing information systems, data technologies, validation practices, and biotech or pharmaceutical environments.

Supports the enterprise data and analytics platform by building Microsoft Fabric lakehouses, warehouses, pipelines, semantic models, and Power BI reporting. Integrates D365, manufacturing, warehouse, supply-chain, IoT, and operational data; develops SQL and DAX solutions; implements data quality, governance, security, monitoring, and documentation; and troubleshoots production issues. The role also supports AI-enabled analytics and collaborates with business teams, vendors, and technical stakeholders in a manufacturing environment.

Lead the technical direction and production operations of Handshake’s data platform, including Airflow orchestration, ingestion, batch and streaming pipelines, BigQuery, Kubernetes, and cloud infrastructure. Build reliable workflow development and deployment paths, improve data resilience and observability, establish data contracts, support AI workloads, troubleshoot incidents, and mentor engineers across application, analytics, ML, and cloud teams.

Designs, develops, and supports scalable ETL pipelines and large-scale data platforms using Python, PySpark, SQL Server, SSIS, and Hadoop technologies. Responsibilities include database performance tuning, data modeling, production troubleshooting, batch scheduling, data-quality controls, CI/CD, secure development, and collaboration across technical teams. The role also involves mentoring developers and evaluating AI-assisted development tools.

Leads the design, development, optimization, and security of very large SQL Server databases and data warehouses. Oversees ETL and Microsoft BI pipeline development, data modeling, performance tuning, code reviews, and access management. Collaborates with DBAs, mentors developers, applies AI-assisted optimization, assesses risks, and drives scalable, reliable data products.