Top Data Engineer Jobs in Portugal

Build and maintain scalable data pipelines and Python automations for ingesting, processing, and enriching data. Integrate SaaS sources via APIs, use Databricks/PySpark/Delta Lake and AI tools to power lead generation, enrichment, deduplication, and entity resolution. Collaborate cross-functionally to translate business needs into automated, production-ready solutions.

Lead design and global rollout of a high-performance core market data and execution platform. Implement and optimize low-latency market data ingestion, normalization, distribution, and execution components in modern C++. Own deployment, monitoring, profiling, and production optimization while collaborating closely with quants and technical traders to enable systematic pricing and trading strategies.

Lead design and global rollout of a high-performance market data and execution Core Platform. Build low-latency ingestion, normalization, distribution, and execution components. Develop tools for quants and traders, own lifecycle from deploy to production profiling and optimization, and collaborate closely with engineers, quants, and traders to iterate on requirements and platform improvements.

Design, build, and maintain scalable Databricks (PySpark/SQL/Delta Lake) pipelines to transform SAP S/4HANA and ECC data into curated, governed data products. Implement data quality, lineage, observability, and access controls (Unity Catalog, Immuta), collaborate with SAP experts and analytics teams, and mentor engineers to deliver production‑grade datasets for analytics and AI/ML.

The Senior Data Engineer will optimize data ingestion pipelines, manage PostgreSQL databases, design ETL processes, and ensure system reliability in a remote-first, collaborative environment.

Design and maintain infrastructure for large-scale multimodal training and evaluation. Collaborate with researchers to build reliable distributed data systems.

This role involves leading data strategy and managing a team to build and maintain multimodal datasets, ensuring data quality and pipeline efficiency.

The role involves bridging machine learning and systems engineering to enhance autonomy performance by optimizing data quality and developing frameworks for synthetic data in autonomous systems.

The Senior Data Engineer will design cloud-based data storage solutions, develop ETL/ELT pipelines, and support AI operations while managing data access layers and governance best practices.

Lead technical design and hands-on development of Pantheon’s data platform, extending ingestion, curation, retention services and ML/LLM infrastructure. Mentor engineers, drive architecture and engineering standards, operate in a DevOps model, partner cross-functionally, and participate in on-call support to ensure reliable, compliant data access and analytics.

Design, build, and optimize end-to-end data pipelines and ETL/ELT processes, enforce data governance and lineage, create enterprise datasets and data models, mentor team members, and implement CI/CD for data deployments to support analytics and advanced analytics use cases.

Build and scale the company's data infrastructure: design ingestion paths, event models, schema-flexible data models, change capture, query performance, freshness guarantees, and analytics serving for customer-facing dashboards and evaluation pipelines.

Design, develop, configure, and support Customer MDM and Informatica Product 360 solutions, including data models, workflows, integrations, data quality, governance, and production support across enterprise systems. Collaborate with stakeholders throughout the SDLC to implement MDM/PIM processes, troubleshoot incidents, and maintain documentation and release activities.

Design and build data models, automated pipelines, and dashboards to support Lunar program planning and technical performance. Partner with stakeholders to gather requirements, create visualizations and metrics for leadership, lead cross-functional data modeling efforts, and establish data quality and documentation standards to scale analytics across programs.

Design and build SOCOTEC's enterprise data platform: scalable Databricks/Spark/Delta Lake pipelines, data models, and MDM. Ingest from ERP/CRM, enable batch and near-real-time processing, ensure data governance, quality, lineage, and provide datasets for analytics and AI while driving architecture and observability.

Design, build, and maintain production-grade data pipelines, Python services, and Databricks workloads for a large-scale financial data platform. Improve performance, reliability, observability, and data models; troubleshoot issues; participate in architecture, code review, and cross-team collaboration to deliver enterprise reporting and integrations.

Design and implement a scalable data platform and integration pipeline to ingest, normalize, and index enterprise data. Build connectors, ETL/streaming pipelines, and storage/indexing strategies to support semantic search and GenAI use cases. Partner with applied AI teams, make build-vs-buy decisions, and create reusable patterns to scale integrations.

Lead software engineer building enterprise applications across the SDLC. Coach and lead small teams, work client-facing to diagnose problems, architect and deliver cloud and data-driven solutions using modern languages, web and mobile frameworks, AI/ML, DevOps, and present solutions to stakeholders in a hybrid model.

The Cyber Data Analytics Engineer designs and maintains data systems to support cybersecurity, ensuring log data compliance and accessibility for government agencies.

Lead technical evaluations and pre-sales activities for data-driven, AI-powered Salesforce solutions. Design data architectures and AI use cases, deliver demos, proofs of concept, and workshops, advise customers on data ingestion/integration and real-time analytics, and collaborate with sales and marketing to drive revenue.

Design, build, and deploy agentic AI solutions (Google Gemini, Claude, ADK); maintain BigQuery data warehouse and ETL pipelines; troubleshoot tracking across Google Analytics, Omeda, Piano, and Salesforce; create dashboards and monitoring to ensure data quality and measure agentic impact across Sales, Marketing, Editorial, and Finance.

The Senior Data Engineer will design and build scalable data platforms, handle automation for data operations, and ensure reliability and performance of data pipelines while collaborating with various teams.

Build and scale Allocate's AWS-based data lakehouse and pipelines (batch and real-time). Model financial entities and integrate internal/third-party sources. Enable ML/AI workflows, vector and knowledge-graph integrations, CI/CD and containerized deployments, and collaborate with engineering to deliver reliable, production-grade data and AI infrastructure.

Lead architecture and implementation of enterprise-scale, production data pipelines and ecosystems for global, customer-facing products. Collaborate with product and engineering leadership, mentor peers, enforce code and CI/CD standards, and optimize data storage and performance for high-availability, defense-focused monitoring solutions.

Design, build, and support full-stack web applications and microservices to provide self-service test data capabilities. Develop Java/Spring Boot backend services and React front-ends, design RESTful APIs, automate test data provisioning, contribute to CI/CD pipelines, and provide production support and engineering best practices across teams.