Top Data Engineer Jobs in Portugal

The Machine Learning Engineer designs and implements scalable solutions for clients, analyzing datasets, productionizing ML systems, and leading teams.

The Machine Learning Engineer designs and implements data-driven solutions, develops scalable ML systems, analyzes datasets, and leads client collaborations.

As a Senior Software Engineer, you will develop distributed data storage and processing systems, enhance performance, and support diverse data workloads at Databricks.

Develop next-gen distributed data storage and processing systems, enhance query performance, and support diverse workloads from ETL to data science.

As a Staff Software Engineer at Databricks, you will develop distributed data storage and processing systems, focusing on projects like Apache Spark, Delta Lake, and performance optimization for diverse data workloads.

As a Software Engineer on Glean's Data Foundations team, you'll build and scale data ingestion connectors, transforming unstructured content into structured data while ensuring system reliability and security throughout the data processing pipeline.

The Sr. Data Engineer will build and manage data pipelines for large datasets, collaborate with teams, and leverage cloud technologies for data processing.

Lead Data Engineer responsible for defining architecture, engineering standards, and best practices for the enterprise data platform, collaborating with distributed teams for modernization and scalability.

Design, build, and maintain scalable data pipelines, ETL/ELT processes, data lake and warehouse infrastructure, and cloud-based data platforms. Optimize systems for performance, reliability, security, and cost while implementing monitoring, governance, and data quality practices. Collaborate cross-functionally with data scientists, analysts, engineering, and product teams to deliver reliable data solutions and improve the data ecosystem roadmap.

Designs, builds, and operates large-scale data acquisition pipelines and backend services. Responsibilities include batch and streaming ETL/ELT, distributed processing, workflow orchestration, data validation, enrichment, deduplication, schema evolution, observability, and cloud infrastructure. The role improves pipeline reliability, performance, scalability, and cost while collaborating with product, data science, platform, and data quality teams.

Lead mechanical engineering evaluations for data center opportunities, assessing HVAC, cooling, chiller, CRAH/CRAC, liquid cooling, and critical equipment systems. Conduct facility due diligence, validate capacity and design assumptions, evaluate vendors and deployment risks, and provide feasibility and Go/No-Go recommendations. Support mechanical design strategies, equipment selection, commissioning, and construction readiness while partnering with engineering teams, consultants, and vendors to establish scalable standards for hyperscale and AI infrastructure.

The Senior Autonomy Engineer will build data pipelines for drone datasets, improve dataset quality, and support autonomy teams with data tools.

Develop distributed backend systems, APIs, and services for data acquisition, access, and processing. Write maintainable Golang services and a Python client library, optimize ingestion and retrieval performance, and collaborate with physicists and engineers to translate requirements into software. The role supports simulation and experimental data analysis in a fusion-energy environment and may involve safety-sensitive work, occasional travel, nights, weekends, or on-call coverage.

Lead the architecture and development of Yahoo’s AI-powered data intelligence platform at petabyte scale. Build distributed batch and streaming systems, production RAG and multi-agent applications, semantic metadata integrations, and evaluation frameworks for retrieval quality, agent accuracy, hallucination prevention, and operational safety. Establish enterprise AI reference architectures, drive adoption across teams, validate AI-generated code and agent plans, and influence technical strategy across engineering, governance, infrastructure, product, analytics, and business stakeholders.

Build and maintain data warehouses, pipelines, scalable data models, and data quality frameworks for Waymo commercialization. Translate business requirements into database models, transform raw data for reporting and insights, ensure PII and ACL compliance, document solutions, and collaborate with data producers and consumers. The role requires SQL expertise, database knowledge, and programming experience in Python, C++, or Java, with preferred experience in distributed data processing and cross-functional project leadership.

Designs and delivers a global analytics platform supporting reporting, visualizations, self-service analytics, and embedded data products. Responsibilities include data collection and processing, semantic modeling, warehouse and pipeline development, query optimization, governance, analytics enablement, and stakeholder collaboration. The role provides actionable insights from complex travel data and builds integrated analytics applications using cloud platforms and business intelligence tools.

Designs, builds, tests, and maintains software and data infrastructure for business-facing solutions. Develops CI/CD and DevOps practices, supports applications throughout their lifecycle, contributes to internal tools and standards, and collaborates directly with end users. Requires Python, SQL, large-scale data engineering experience, Azure and Databricks knowledge, and familiarity with Power BI, Copilot Studio, and AI tools.

The Staff Software Engineer will architect and implement scalable data systems, collaborate with teams, mentor engineers, and ensure data integrity.

Designs and maintains scalable data pipelines and platforms, develops ETL/ELT processes, and migrates heterogeneous external data into standardized enterprise models. The role includes data ingestion, transformation, quality validation, reconciliation, and billing-data standardization across systems. It collaborates with engineering, product, DevOps, and DBA teams, contributes to technical decisions, mentors engineers, and applies AI-assisted development tools. The position is based in Richmond, Virginia, with four days in office and one day remote.

Own Doctronic’s end-to-end data platform, including CDC pipelines from production databases into S3, Iceberg, and Snowflake; dbt transformations; orchestration; warehouse architecture; monitoring; and governed access to PHI. Establish trusted, documented data layers for analytics, finance, dashboards, and AI model training. Implement HIPAA-compliant access controls, anonymization, and deletion workflows while partnering autonomously with product, finance, marketing, partnerships, and AI teams.

Designs, builds, and maintains scalable AWS data pipelines, integrations, lakehouse infrastructure, and Airflow workflows. Processes commercial pharmaceutical data, supports pharma KPIs and analytics, and develops pipelines for AI, machine learning, generative AI, LLM, embeddings, and RAG applications. The role also includes legacy-system migration, pipeline monitoring and optimization, data quality assurance, and translating pharmaceutical business needs into reliable data solutions.

Design and implement end-to-end AI features, scalable data pipelines, ETL/ELT workflows, Generative AI and agentic systems, ML and BI solutions, and MLOps/LLMOps practices across AWS, Azure, and GCP. Apply RAG, embeddings, vector databases, security governance, evaluation, reliability, and guardrails. Own technical workstreams, mentor junior engineers, and promote software engineering best practices in consulting environments.

Analyzes product design, reliability, maintenance, and operational performance; recommends design, material, tooling, cost, and service improvements. Provides advanced technical support for complex mechanical, electrical, and hydraulic issues, prepares field damage assessments and corrective-action reports, supports product notifications and factory acceptance tests, and contributes to training and competency programs. Collaborates globally with product engineering, specialists, customers, and technical support teams while ensuring ISO 9001, HSE, and company quality compliance.

Design and scale Zip’s enterprise data and AI platform across batch, streaming, structured, and unstructured workloads. Build reliable pipelines, AI-ready data products, semantic models, vector and hybrid search, and RAG capabilities. Establish standards for modeling, testing, governance, security, observability, and automation. Partner with engineering, data science, product, and business teams while mentoring engineers and influencing platform architecture.

Designs and leads scalable real-time and batch data pipelines, data platforms, architectures, data products, and intelligent APIs. Ensures data quality, supports BI and AI/ML initiatives, and develops ingestion, processing, migration, and analytical solutions for big data, NoSQL, and data warehouse environments. Provides technical leadership, mentorship, code reviews, testing, CI/CD implementation, system monitoring, troubleshooting, and cross-functional translation of business requirements into reliable cloud-based solutions.