Top Data Engineer Jobs in Portugal

Lead design and delivery of API and data engineering solutions: build end-to-end data pipelines, develop ontologies and schemas, ensure data quality and governance, integrate systems (including cloud/GCP), enable AI capabilities, enforce security/compliance, and mentor/lead technical teams within an Agile consulting environment.

Design and build an end-to-end, high-throughput dataloading stack for massive multimodal datasets: formatting, preprocessing, filtering, sharding, caching, and streaming data to distributed GPU training with observability, reliability, and performance benchmarking.

Design, build, and maintain a production data platform for research: ingestion, ETL/ELT, object stores, SQL and NoSQL schema design, indexing, query optimization, observability, and high-throughput data movement. Collaborate with researchers, ML engineers, and infra to produce reliable interfaces for analytics, model training, and long-term archival while optimizing performance and maintainability.

Lead data engineering for a healthcare scheduling platform rebuild: map legacy multi-TB schema, design target schema, build translation layer (views/materialized views and write mappers), ensure data consistency during parallel systems, plan per-tenant cutover with verification and rollback, tune DB performance, instrument data quality/lineage/audit, and mentor engineers.

Design, develop, and maintain large-scale data pipelines and ETL processes. Implement and optimize data storage and processing on BigQuery/GCP, ensure data quality and monitoring, participate in code reviews, mentor junior engineers, and help launch data-driven tools.

Support cyber security compliance by analyzing vulnerability, authorization, and configuration data; transform and import data for visualization tools; produce metrics and graphical reports for IA compliance; maintain Excel-based visualizations; collaborate to simplify and automate the Heat Map.

Support cyber security operations by compiling reporting metrics, validating network/system security, assessing vulnerabilities, producing threat analyses and mitigation recommendations, participating in design reviews and cyber defense groups, and preparing briefings and documentation for senior US government intelligence and operations officials.

The R&D Engineer Intern will design machine learning pipelines, translate research into products, and develop microservices for biomedical engineering applications.

Lead design, build, and operate scalable, low-latency data systems and platform services for real-time personalization and recommendations. Partner with ML, product, and platform teams to deliver feature serving, inference integration, APIs, monitoring, and reliability. Provide architecture leadership, mentor engineers, and establish operational standards for data pipelines and ML workflows.

The Data Systems Engineer will support data integration, pipeline development, metadata tagging, and data governance in a fast-paced environment, collaborating with technical and business teams to ensure data quality and system interoperability.

Lead and deliver complex data science and mathematical projects for DoD clients: design ML and statistical models, develop algorithms, perform EDA, integrate solutions, create dashboards and reports, mentor staff, and ensure compliance with DoD standards while driving research and innovation.

As a Software Engineer in EHR Integrations, you will design, develop, and maintain software for EHR integration, clinical workflows, and data governance while collaborating with product managers and security teams.

Design, build, and scale reliable batch and real-time data pipelines and warehouses. Partner with engineering, data science, and business teams to define data models, improve observability, optimize storage and querying, and evangelize data engineering best practices across the company.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

Design and build operational data systems, including pipelines, storage layers, and APIs for near real-time enforcement and insights, balancing streaming and batch paradigms.

Design, build, and maintain data ingestion pipelines and integrations from intermittently-connected robots to analytics, ML training, and operations. Implement SDKs, connectors, schema contracts, retries, backfills, monitoring, and optimize pipeline performance, scalability, and cost. Collaborate with robotics, autonomy, and deployment teams to ensure reliable end-to-end data delivery and quality.

Build and operate the cloud foundation for the data platform: design compute, storage, and networking; manage IaC and GitOps; provision for large-scale sensor and ML workloads; own reliability, security, observability, cost management, and internal tooling to enable pipeline and analytics teams.

Design and build a scalable data platform and tooling for robotics/autonomy data ingestion, integration, and delivery. Build SDKs, connectors, and APIs (REST/gRPC, webhooks, CDC) to integrate diverse sources and downstream ML/BI systems, ensure schema/versioning/reliability, and optimize pipeline performance, scalability, and cost.

Lead the architecture of core data processing systems for Snowflake, focusing on distributed systems and high-performance data transformation, ensuring efficiency and reliability at scale.

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.

As a Data Engineer, you'll architect and build large-scale data infrastructure for real-time search, handling massive data volumes efficiently.

Lead design and delivery of customer-facing data product applications, building full-stack experiences (frontend, backend, APIs) using TypeScript, React, Node.js, and Python. Partner with Product and data teams to convert analytics and prototypes into production-grade workflows, establish software engineering best practices, mentor engineers, and prioritize customer value through testing, observability, and operational ownership.

The Staff Data Engineer will design and enhance data architectures, lead complex initiatives, mentor teams, and ensure data quality and governance across the organization.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

The Senior Software Engineer will focus on Lucene's distributed indexing and query capabilities, improve code features, and collaborate with a global team.