Top Data Engineer Jobs in Portugal

Own and operate Priority Waste’s enterprise data platform, building Azure and Microsoft Fabric pipelines, warehouse models, Power BI semantic models and dashboards. Integrate operational, payroll, fleet, telematics, API and file-based data sources. Manage monitoring, alerting, data quality and governance while expanding AI-driven reporting and reconciliation automations. This hands-on, on-site role requires independently scoping, building, deploying and operating production data systems as the company’s primary data engineer.

Designs, builds, and optimizes batch and real-time data pipelines, warehouses, streaming solutions, analytical data models, and containerized data services. The role integrates diverse data sources, automates workflows, deploys secure multi-cloud services, embeds security scanning and encryption into CI/CD pipelines, and collaborates in Agile teams while mentoring junior engineers. Required expertise includes Spark, Kafka, Airflow, cloud data platforms, Python or related languages, databases, data modeling, Docker, and Kubernetes.

Lead the engineering modernization of enterprise data protection and DLP capabilities across cloud, SaaS, endpoints, email, and collaboration platforms. Build automated Policy-as-Code workflows, CI/CD pipelines, reusable controls, integrations, detection logic, guardrails, and operational metrics. Partner with technical, compliance, privacy, legal, and business teams to improve security effectiveness, reduce false positives, automate governance, investigate events, and demonstrate measurable risk reduction.

Senior Software Engineer joining Fetch’s Data Platform team to architect and evolve scalable data pipelines, governed data access, delivery infrastructure, and partner integrations. The role owns ambiguous technical problems, leads multi-system initiatives and migrations, improves reliability and engineering efficiency, shapes technical direction, collaborates across teams, and mentors engineers. Candidates need strong backend or platform engineering experience, data infrastructure knowledge, cross-team leadership, operational judgment, and excellent communication skills.

Lead the design, development, and optimization of scalable batch and real-time data pipelines and platforms. Build cloud-based data solutions using distributed processing, streaming technologies, and modern data warehouses. Define data models, improve performance and reliability, establish engineering best practices, and provide technical guidance to data engineers while collaborating with architects, product teams, developers, and stakeholders.

Design and maintain healthcare data integration pipelines, models, and validation processes for claims, billing, clinical, pharmacy, EMR, FHIR, and value-based care data. Collaborate with clients and internal analytics, product, and customer success teams to interpret data, document business rules, support implementations, and build reusable Ursa data models. Apply healthcare domain expertise, data security practices, HIPAA compliance, and appropriate judgment when using AI-assisted tools.

Develop and maintain big data solutions using Hadoop, Spark and Scala. Work with Kafka and Cassandra for data streaming and storage. Require hands-on experience on large projects, strong debugging skills, and log analysis to diagnose production issues.

Design and scale real-time security data pipelines: stream processing, log parsing/enrichment, schema normalization (OCSF/ECS), and cloud data lakehouse optimization, integrating LLMs to accelerate pipeline development and query optimization for threat hunting and security operations.

Design, build, and maintain ELT and streaming data pipelines; operate Dagster/Airflow and dbt workflows; own Snowflake schemas and data quality; resolve data incidents; contribute to architecture, documentation, analytics tooling (Hex, AI agents), and participate in on-call rotation.

Design and build scalable, cloud-native backend services and AI-powered applications. Implement agentic AI solutions and integrate LLMs with enterprise systems. Develop REST/GraphQL APIs, microservices, and event-driven architectures. Deploy on AWS, containerize with Kubernetes/Docker, build CI/CD pipelines, and ensure observability. Collaborate with cross-functional teams to deliver secure, high-performance enterprise solutions and leverage AI-assisted developer tools.

Design and build cloud-native, scalable data solutions for systematic trading. Partner with traders, quants, and architects to develop Snowflake-based ETL, data models, and pipelines; lead AI-driven capability adoption; ensure security and SDLC best practices.

Develop, maintain, and improve thermofluid lumped-parameter models for the Raptor engine; perform cycle analysis, anomaly root-cause work, and integrated vehicle simulation support; build tools, automation, and data pipelines to translate test data into performance predictions for tests and flight software (GNC).

Design and deliver graph and semantic capabilities for ArcGIS by working with users, product and engineering teams to build, test, and release graph databases, graph analytics, and GeoAI integrations for Web GIS and ArcGIS Enterprise.

Lead design and implementation of a scalable enterprise data warehouse: dimensional modeling, ETL/ELT pipelines, cloud data platforms, data governance, performance tuning, monitoring, and mentoring. Collaborate with stakeholders and engineering teams to enable analytics, ensure data quality and security, and support data science/ML workloads including feature engineering and NLP components.

Lead the architecture, design, and implementation of a high-performance data processing engine focused on large-scale data processing.

The Staff Engineer will lead technical direction on data infrastructure, focusing on ingestion frameworks, storage architecture, and orchestration to support scientific workflows. Responsibilities include mentoring, ensuring reliability, and collaborating with cross-functional teams to establish coding standards and data integrity.

Design and deliver data-driven AI solutions and architectures, lead technical proofs-of-concept, drive technology transformation, manage stakeholder relationships, ensure data security and PII management, contribute on Agile teams, and guide global cross-team implementations to meet strategic business outcomes.

Lead and scale in-house data operations for robotics R&D: build and maintain data tooling and sensor hardware, run collection and annotation, manage interns/contractors, write SOPs and QA, and support demos and live troubleshooting.

Design, build, and operate large-scale ETL pipelines to turn high-volume raw data into production-grade datasets for reporting and measurement. Own data products end-to-end from requirements through implementation, validation, and production rollout, collaborating with data science, backend/frontend engineers, and product. Ensure data quality, performance tuning, and operational reliability.

Design, build, and own large-scale ETL pipelines to produce production-grade analytics datasets. Translate requirements into specs, implement and validate data products, ensure data quality, debug distributed systems, and collaborate cross-functionally with data science, backend, frontend, and product teams for production rollouts.

Design, build, and operate large-scale ETL pipelines on Databricks/Delta Lake to produce curated analytics datasets. Collaborate with data science, backend/frontend engineers, and product from requirements through production, ensuring data quality, validation, performance tuning, and incident resolution.

Design, develop, test, and maintain mission data for airborne electronic warfare systems. Lead mission data engineering efforts including emitter definition programming, simulation and lab verification, rapid reprogramming, and stakeholder coordination. Provide technical leadership during system test and evaluation and mentor junior staff.

Lead data engineering work across migrations, pipelines, integrations, and APIs. Design, build, deploy, test, monitor, and support production data solutions while ensuring data quality, validation, and adherence to architectural standards in an agile continuous-delivery environment.

The Senior Data Engineer designs and maintains data pipelines, ensuring data quality for analytics while collaborating across teams and guiding others.

Lead design and optimization of data-intensive, distributed backend systems for query, search, and AI data products. Improve query plans, indexing, caching, and schema/access patterns to reduce P95/P99 latency and scale reliability. Drive architectural improvements, operate JVM-based services, and raise technical standards via design reviews and cross-functional collaboration.