Top Data Engineer Jobs in Portugal

Develop and implement a data management strategy, oversee data governance and architecture, ensure compliance, and manage vendor relationships to support organizational goals.

The Senior Data Engineer will standardize and reuse data, develop features, create ETL processes, and collaborate with cross-functional teams.

Design and implement cloud-native data pipelines and metadata readers on OCI, build AI agents and integrate mission data with LLMs using RAG/MCP, develop production geospatial solutions, create Node.js dashboards connected to Oracle Databases, and ensure secure, scalable cloud architectures for defense customers.

Design, build, and scale cloud lakehouse data products (Databricks/Snowflake) from ingestion to analytics-ready datasets using medallion architecture. Develop reusable Python frameworks, Spark pipelines, and dbt/SQL transformations. Implement data modeling, governance, observability, validation, and SLA monitoring. Troubleshoot production issues, adopt AI to accelerate engineering, and provide technical leadership, code reviews, architecture decisions, and mentoring for global engineering teams.

Lead design, management, testing, and real-time support of LEO satellite data handling subsystems. Develop and maintain operations procedures, scripts, and tools; perform telemetry monitoring, anomaly detection, recovery, and commanding. Support onboard algorithm development and troubleshooting; ensure satellite safety and operational readiness.

As a Backend Engineer, you'll build backend services for candidate-job matching and marketplace workflows, focusing on APIs, data models, and operational systems.

Design, build, test, and maintain high-quality data pipelines and storage systems. Collaborate with architects, analysts, scientists to enable data ingestion, transformation, real-time analytics, and data reliability. Write efficient code, unit/integration tests, and apply DevOps/SDLC practices while ensuring data security and cloud infrastructure best practices.

Lead design and delivery of scalable data platforms and pipelines on Google Cloud. Build and review Python/SQL code, drive data architecture using BigQuery and GCP tooling, own ingestion/transformation/orchestration, lead client technical discussions, prototype solutions, mentor engineers, and implement IaC, CI/CD, observability, and governance.

Design, build, and run data-heavy features for financial products, improve data models, pipelines, migrations, and multi-tenant systems. Work in a TypeScript monorepo, operate serverless AWS infrastructure, integrate LLM APIs, monitor production, and lead pragmatic technical decisions.

Lead design, build, and operate a secure, scalable data platform to support analytics, MLOps, and BI. Architect data warehousing (Databricks, dbt, Spark), build ETL pipelines, optimize cloud storage and processing in GCP/AWS, implement LLM infrastructure and serving, create observability and BI dashboards, and ensure data governance and regulatory compliance (HIPAA/SOC-2). Collaborate with Data Science, ML, App, and DevOps teams.

Lead development, tuning, and optimization of incrementality and attribution models for podcast advertising. Build, test, and refine statistical models on large datasets, collaborate with product and data teams, translate findings into actionable insights, and improve measurement methodologies to quantify ad impact.

Design, build, and maintain production-scale data systems and web-scale datasets (Spark/Flink) to support personalization ML. Drive dataset/schema design, collaborate with algorithm teams, and improve distributed big-data processing for member experience.

Design and operate large-scale data platforms in the cloud, develop data pipelines, support analytics and machine learning, and mentor junior engineers.

Design, build, and operate production-grade realtime and batch data pipelines and internal data products. Ensure data correctness, tooling for backfills and reports, and partner with product/business teams to prioritize data acquisition and improvements. Work across query engines and streaming frameworks to support analytics, monitoring, and debugging for product and business stakeholders.

Design, build, and maintain scalable Python-based ETL/ELT data pipelines and Airflow workflows implementing Medallion (Bronze/Silver/Gold) Lakehouse patterns. Ensure data quality, performance tuning, monitoring, CI/CD, and cross-team collaboration to support analytics, reporting, and ML use cases while adhering to governance and security standards.

Provide technical leadership to design, develop, integrate, and support enterprise customer-data solutions using Salesforce Data Cloud and related cloud, API, and streaming technologies. Mentor junior engineers, collaborate with stakeholders, perform root cause analysis, and document solutions across front-end, back-end, and data layers.

Technical leader for Data Engineering responsible for designing, operating, and optimizing Snowflake-based data platforms, self-hosted orchestration (Prefect), dbt practices, AWS infrastructure, and data pipelines. Drive architecture, mentor engineers, partner cross-functionally, ensure observability and production-grade practices, and enable model-ready datasets and AI/LLM workflows.

The AV Safety Data Reporting Engineer will support safety data reporting and compliance by analyzing large datasets and improving reporting processes across teams.

Design, build, and scale the data platform that converts raw mass-spectrometry and biochemical data into validated, labeled datasets. Own pipelines, data contracts, serving, cost optimization, quality gates, SDKs and interfaces, and operational SLAs. Collaborate with ML researchers, scientists, and product to enable model development and product features.

Own and improve annotation systems, workflows, and tooling to produce high-quality training data. Build Python and web tools, integrate model-assisted labeling and active learning, implement data quality checks, support dataset versioning and evaluation, and coordinate cross-team efforts to measure and improve annotation throughput and model impact.

Build and operate production pipelines that convert raw infrared satellite frames into calibrated, orthorectified, analysis-ready products. Optimize pipeline latency and scale, implement workflow orchestration, build monitoring and operational tooling, collaborate with remote sensing scientists to productionize algorithms, participate in on-call rotations, and diagnose and fix data quality and processing failures.

Design, build, and operate data infrastructure and pipelines that ingest large-scale vehicle sensor logs into cloud storage, curate datasets and labeling workflows for ML training, deploy visualization tooling for log review and QA, implement validation/monitoring and data lifecycle policies, and collaborate with autonomy teams to define data contracts and support model training and evaluation.

Design and implement scalable backend systems for Patreon's platform. Collaborate with engineers and product managers to maintain and optimize performance.

Lead design, development, integration, and maintenance of scientific data processing systems. Define requirements, create prototypes, execute integration and acceptance tests, manage schedules and configuration changes, evaluate vendor software, conduct trade studies, and mentor engineers while ensuring quality, security, and compliance with systems engineering processes.

Design, build, and operate controlled ETL/ELT pipelines and reconciliations between Delphi, ServiceNow, and PRISM. Maintain common-key mappings, enforce data-quality assertions, implement row/column access controls, manage exception queues, and produce documentation and runbooks enabling government staff to reproduce results independently.