Top Data Engineer Jobs in Portugal

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.

Lead design and optimization of data-intensive distributed systems and query infrastructure. Improve query plans, indexing, caching, and schema/access patterns to reduce P95/P99 latency, ensure scalability, and support AI-powered data products. Mentor through design reviews and operate backend systems in the JVM ecosystem.

Build and operate large-scale backend data pipelines and ETL/ELT workflows for ingesting, validating, normalizing, enriching, and storing high-volume data. Implement Java-based services, batch and streaming processing (Beam, Spark, Dataflow), orchestration (Airflow), and cloud infrastructure (GCP). Improve data quality, observability, and reliability while collaborating with product and platform teams to deliver production-grade data acquisition solutions.

Lead design and implementation of products, mentor engineers, drive innovation, and build scalable data solutions using modern tech stack.

Design, integrate, maintain, and troubleshoot vehicle electronics and data acquisition systems for race and test events. Responsibilities include harness and instrumentation design, device programming, CAN communications, data processing, test planning, trackside installation and support, telemetry monitoring, documentation, supplier coordination, and inventory/maintenance tracking. Frequent collaboration and travel to races/tests required.

Design, implement, and maintain data security controls and safeguards across data platforms. Manage access controls, perform risk assessments, implement encryption and DLP, respond to incidents, support compliance and audits, document controls, and deliver data security training in coordination with data governance and compliance teams.

Customer-facing cloud security presales engineer who consults with executives and security teams, develops security services and lab-based use cases, educates sales, creates collateral, and stays current on security technologies and frameworks to support sales engagements.

Build and maintain scalable security platforms, automation, and tooling to protect data across SaaS, cloud, endpoints, collaboration tools, AI systems, and data warehouses. Develop data discovery, classification, governance, DLP, DSPM/SSPM, insider-risk, and access controls; leverage AI and automation to improve detection, prevention, and incident workflows while partnering with cross-functional teams.

Design and implement enterprise data security architectures focused on databases (SQL Server), Databricks, and object storage. Develop encryption, IAM, DLP, IRM/DRM, tokenization, and SecOps controls; secure data pipelines, perform vulnerability assessments, automate security tasks, and maintain policies and documentation while collaborating with development teams.

Implement and support data and system security measures focusing on encryption and PKI. Manage encryption tools (Vormetric, CloudLink), administer PKI solutions (ADCS and external providers), troubleshoot security issues, and provide customer-facing support and investigative problem solving.

Design, develop, deploy and support the bank's data security capabilities (DLP, email encryption). Build Splunk dashboards/alerts/reports, implement use cases, test, document, troubleshoot production issues, and coordinate with teams and vendors for change requests and maintenance.

Lead design, deployment, operation and enhancement of data security capabilities (DLP, email encryption, key management). Develop rules from business requirements, run product evaluations/POCs, manage upgrades, incident response, audits, vendor coordination, and continuous improvement to reduce data leakage risk.

The Staff Data Engineer will design and implement data architectures, manage partner integrations, build scalable data solutions, and mentor team members, ensuring efficient data operations and collaboration across teams.

Lead the design and implementation of scalable data architecture and engineering solutions, manage partner integration, mentor engineers, and ensure best practices in data systems.

Design and build data infrastructure and AI/ML systems—extracting, cleaning, moving, and storing data; develop, deploy, and monitor ML and LLM-based products; build APIs; collaborate with stakeholders and manage projects to meet business needs.

Build and maintain the core robot software stack including communication, state management, data transport, deployment tooling, and hardware interfacing. Develop tooling, telemetry, data pipelines, and reliability features. Collaborate across controls, perception, ML, and hardware teams and shape scalable system architecture.

Design, build, and operationalize secure data pipelines and analytics for Naval and DoD missions. Develop event-streaming and distributed systems, normalize multi-format data, deploy cloud-native and containerized solutions, work with GIS and operational environments, and collaborate with cross-functional teams while meeting shipboard and Navy safety requirements.

Design, implement, and operate data/platform infrastructure for digital products. Architect cloud-native and hybrid networking, ensure availability and performance, lead DevOps practices, drive automation, monitor systems, support incident response, and collaborate with product and IT teams to meet SLAs and compliance requirements.

Build and scale backend services for identity, access control, secure content sharing, and data access. Contribute to Dgraph internals, collaborate with platform and infrastructure teams, drive architecture and permissions models, and write high-quality Go and Python code focused on reliability, security, and performance.

Design, build, and scale data-driven solutions and high-volume ETL/ELT pipelines for equity research. Develop cloud-based (AWS) data architectures, ensure data modeling, governance, performance tuning, and collaborate with data scientists and business partners in Agile environments.

The Data/ML Infrastructure Engineer builds and operates data infrastructures for processing drone and orbital sensing data, ensuring reliability, observability, and performance while collaborating with research and product teams.

As a Founding Data Scientist, you will develop predictive models and optimize data infrastructure to enhance supply chain operations, focusing on shipment risk and decision-making.

Work with implementations to migrate customer data into the MemberSuite SaaS platform. Develop C#/ASP.NET tools, write SQL queries, use database management tools and SQL Server, troubleshoot data issues, meet deadlines, and coordinate with stakeholders to deliver migration projects.

Design, build, and scale open-source data infrastructure across collection, ingestion, storage, querying, and retrieval. Improve ingestion pipelines, expose performant query interfaces and integration hooks, and deploy reliable data platform features across cloud, hybrid, and on‑prem environments.