Top Data Engineer Jobs in Portugal

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.

Leads technical solution design and data engineering initiatives, developing ETL processes, data pipelines, cloud data solutions, monitoring, documentation, and compliance-by-design practices. Performs data exploration and profiling with Databricks, supports testing and deployment, and collaborates with product owners, stakeholders, governance, and architecture teams. Provides technical leadership across multiple projects, promotes reliability and recovery practices, and manages cross-functional collaboration in a banking environment.

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.

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.

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.

Lead the design, provisioning, automation, and operation of an Azure- and Snowflake-based cloud data platform. Build IaC, CI/CD pipelines, orchestration and monitoring, API integrations, and scalable data pipelines. Troubleshoot platform issues, optimize performance and costs, collaborate with architects and business partners, mentor engineers, and drive modernization to Snowflake/Databricks.

Responsible for application systems analysis, design, and programming. Engage in system implementation, user support, and project management while recommending advanced programming solutions and security measures.

Build and maintain data lakes, data warehouses, and modern data pipelines for a multi-tenant SaaS platform. Design end-to-end data processes, write pipeline and infrastructure code, conduct design reviews, optimize performance, monitor systems, support data governance, and troubleshoot scalability and security issues. Collaborate with technical and business stakeholders, mentor junior engineers, evaluate technologies, document platform architecture, automate testing, and participate in on-call rotation.

Design and build a company-wide data platform supporting ingestion, CDC, replication, transformation, governance, semantic discovery, analytics, and self-service dbt workflows. Develop scalable architectures across distributed SQL databases and analytical platforms, establish data quality and observability standards, implement access controls and metadata foundations, and provide technical leadership across engineering teams. The role also shapes source-of-truth architecture and enables data for AI and agentic applications.

Develops, tests, deploys, refactors, and supports production software for enterprise data warehousing. Builds ETL and data engineering solutions, creates automated test suites, monitors performance, and contributes to security and resilience. Collaborates in agile product teams, helps define testable user stories, evaluates tools, and mentors junior engineers through technical guidance and discussions.

Build and support backend services and production data pipelines for cyber platforms. Design data ingestion, modeling, transformation, validation, storage, and recovery systems. Develop Python testing frameworks, reusable tooling, test environments, CI/CD checks, diagnostics, and documentation. Collaborate with operators and engineers to clarify requirements, make technical decisions, deliver production software, and establish scalable testing practices.

Design, build, and operate WHOOP’s data platform infrastructure, including lakehouse, warehouse, and streaming systems. Improve performance, reliability, cost efficiency, observability, and developer experience across AWS-based data systems. Develop internal tools, APIs, automation, CI/CD, and infrastructure-as-code practices. Partner with data, ML, analytics, and software engineering teams to support scalable workflows, governance, and production excellence while using AI-assisted development tools effectively.

Own the architecture, roadmap, and operation of Clarium’s AWS-based data platform. Build reliable batch and near-real-time pipelines, model healthcare supply chain data, optimize Postgres and Snowflake performance, and establish standards for testing, deployment, quality, and governance. Partner cross-functionally to create durable data models, lead multi-quarter initiatives, manage sensitive data controls, and mentor engineers.

Execute ETL workflows supporting large-scale migration from legacy systems to cloud environments. Extract, transform, cleanse, validate, and load structured and unstructured data; monitor pipelines; troubleshoot defects; and support automation, quality controls, staging, testing, and cutover operations. Maintain data maps, logs, procedures, and technical documentation while collaborating with data, cloud, QA, and product teams in a federal modernization program.