Top Data Engineer Jobs in Portugal

Design, build, and maintain interactive Power BI and MicroStrategy dashboards supporting IT operations. Perform ETL and data integration, query complex databases, validate data accuracy, ensure DoW compliance (STIGs, IL5/6/7), collaborate with stakeholders, document standards, and train users to translate data into actionable insights.

Build and maintain Geotab's internal machine learning and generative AI platform. Implement logging, monitoring, and alerting; enrich big data with telematics at scale; support data integration and infrastructure for data scientists; document architecture and processes; assist internal teams with AI platform adoption and production deployments.

Build, operate, and modernize a cloud-native enterprise data platform powering SaaS AI products. Responsibilities include data ingestion, storage, querying, quality, governance, and operational excellence, collaborating with engineers to deliver scalable, maintainable solutions and refactor legacy systems.

Design, build, migrate, and maintain scalable data pipelines and architectures on Azure and Microsoft Fabric. Implement ETL/data integration, semantic models for analytics, CI/CD, monitoring, security controls, cost optimization, and testing. Collaborate with cross-functional teams and clients to translate business requirements into reliable, compliant data solutions.

Lead technical pre-sales engagements for Microsoft cloud database and analytics products. Deliver PoCs, demos, hackathons, and architecture workshops; design secure, scalable solutions; resolve technical blockers; collaborate with engineering; and evangelize Fabric, Databricks, Purview and Azure database technologies to accelerate customer migrations and adoption.

Design, build, and operate high-throughput real-time and batch data pipelines and analytics systems. Prototype and deploy data features, ensure data consistency, observability, and performance, and drive architecture and ownership while mentoring engineers and collaborating with product and infrastructure teams.

Design, build, and operate large-scale Hadoop-based data pipelines and analytics platforms. Ingest, transform, and analyze structured and unstructured data to support analytics, ML, and reporting. Ensure reliable, performant production systems and troubleshoot, document, and optimize data workloads.

Lead architecture and engineering for enterprise healthcare data platforms. Design and implement scalable data warehouses, lakehouses, ETL/streaming pipelines, data governance/security, APIs, and infrastructure as code. Advise stakeholders, mentor teams, optimize performance and costs, and ensure compliance with clinical data standards (FHIR, HL7, OMOP) while delivering reliable data products for internal and external users.

Build and maintain governed, activation-ready marketing data products in Snowflake. Design canonical marketing data models, event-streaming, identity resolution, quality checks, and reverse-ETL activation for marketing, CRM, paid media and AI use-cases. Enable predictive scoring, attribution, and AI-ready context layers while partnering with cross-functional stakeholders.

Design and implement data integration and data warehouse solutions using big data technologies. Build cost-efficient, performant cloud data pipelines, apply data modeling and machine learning knowledge, and implement real-time streaming and aggregation patterns.

Lead technical ownership of the SQL Server data warehouse, replication architecture, ETL/ELT pipelines, and Power BI analytics. Design scalable relational models, optimize SQL Server performance, build and maintain semantic models and reports, establish data governance, and translate business needs into reliable, actionable reporting solutions across departments.

Lead design, deployment, and operational support for enterprise data protection across hybrid cloud and on-prem. Focus on encryption, tokenization, key management, HSM operations, integrations with apps and storage, automation via IaC, incident response, vendor strategy, and troubleshooting. Partner with application and infrastructure teams to ensure secure, stable production data protection and compliance.

Build and integrate deep learning models into software pipelines, collaborate with product and engineering teams, support data ETLs, and deploy solutions to cloud-hosted environments.

Provide technical service and support for AI data center systems, including installation, maintenance, troubleshooting hardware and software, and collaborating with clients to ensure high-performance enterprise computing operations.

Lead human-centered design and front-end engineering for the NIH Data Lakehouse: conduct user research and testing; create wireframes, prototypes, flows, and accessible interfaces; build scalable React/Next.js/TypeScript UI components; integrate with GraphQL and search services; contribute to design systems, component libraries, and platform-wide front-end best practices.

Design, build, and optimize scalable data pipelines and architectures using SQL and AWS big-data technologies. Assemble complex datasets, automate processes, enable analytics and stream processing, secure cross-region data, and support cross-functional stakeholders including data scientists and product teams.

Support early-stage project development and feasibility for electrical infrastructure projects. Perform development-phase engineering, system performance modeling, CAD work, cross-discipline coordination, QA/QC, proposal support, client technical communication, and tool improvement. Provide pre-sales technical support and contribute to business development activities.

Perform detailed physical substation engineering for data center projects under a licensed PE's supervision. Produce designs, drawings, specs, ampacity and conduit calculations, QA/QC, coordinate multidisciplinary work, and occasionally perform field inspections and construction supervision.

Design, program, test, install, and commission SCADA, relay, and PLC systems (primarily SEL/RTAC). Produce schematics, configuration files (IEC61850, DNP3, MODBUS), AutoCAD drawings, perform field commissioning/troubleshooting, and prepare project documentation. Support clients and perform periodic interstate field assignments.

Lead ETL and data architecture for AML, trade/sales surveillance, and compliance data repositories. Design and develop complex Informatica PowerCenter 9.1 mappings, enforce ETL architecture standards, tune performance, automate and maintain ETL utilities, collaborate with BAs and DBAs, provide production support, and mentor junior ETL developers.

Design and implement large-scale data processing solutions (GB/PB) using Hadoop, NoSQL, MPP and related open-source tech. Participate in architecture/design, provide implementation details to offshore teams, produce whitepapers/case studies, ensure timely quality deliveries, and share knowledge through training sessions.

Designs and implements large-scale data solutions using Java and open-source big data technologies (Hadoop, NoSQL, Solr, Storm, Kafka). Participates in architecture and design discussions, delivers implementations, collaborates with senior architects and offshore teams, authors technical papers, and shares knowledge across the organization while ensuring performance, scalability, and timely quality delivery.

Work on client onboarding/migration as a Data Analyst/Database Developer: gather business requirements, perform data analysis, mapping, profiling and query optimization. Coordinate with US/UK/India teams and vendors, ensure data quality via control scripts, identify source systems and eliminate redundancies. Assist BUAT, train new resources, and support extracts, views, and client reports. Financial services domain expertise required.

Design, implement, and maintain enterprise database solutions and Big Data (Hadoop) systems. Lead database architecture, HA/DR, migrations, patching, performance tuning, security, capacity planning, monitoring, and incident recovery. Provide technical leadership, SOP documentation, and support BI/data mining activities. Role requires shift work.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.