Top Data Engineer Jobs in Portugal

Design and implement credit underwriting processes while applying quantitative analysis, data mining, and experimentation to understand user behavior and product impact. Collaborate with Product and Engineering to identify trends, solve problems, and guide strategy. Mentor teammates and promote data-driven decision-making across the company.

Build and modernize Carrum Health’s data platform by developing Python and SQL pipelines, AWS services, Terraform infrastructure, dbt transformations, observability, testing, and CI/CD. Automate carrier integrations, reduce operational toil, improve reliability, and support Databricks adoption. Extend AI-assisted ingestion and classification using Bedrock and collaborate across engineering, analytics, data science, and client-facing teams. The role includes production ownership, incident response, technical documentation, and healthcare data platform development.

Build and improve data products, reporting layers, integrations, workflow tools, dashboards, and product-facing data features. Translate ambiguous business needs into maintainable technical solutions, improve data reliability and accessibility, and support analytics, experimentation, segmentation, personalization, and reporting. Collaborate with engineering, product, marketing, e-commerce, and business systems teams while documenting data logic and identifying reusable capabilities.

Build and maintain cloud data architectures, SQL Server databases, data pipelines, models, Power BI solutions, and .NET applications. Lead database modernization and Azure migrations, implement security and DevOps practices, integrate APIs, apply AI and advanced analytics, and ensure data quality, governance, reliability, and cost efficiency. Collaborate with stakeholders and produce technical documentation.

Build and maintain scalable data pipelines and distributed processing solutions supporting analytics, reporting, and machine learning. Develop cloud-based Big Data platforms using Python, Spark, Hadoop, and AWS or GCP. Apply data quality, governance, monitoring, and automation practices; collaborate with architects, data scientists, and analytics teams; participate in Agile delivery and production support; and mentor junior engineers.

Designs and implements scalable software solutions, develops maintainable features, resolves bugs, optimizes performance, and writes automated tests. Participates in architecture discussions, code reviews, Agile planning, CI/CD, observability, and adoption of AI-assisted engineering tools. Collaborates with QA, Product Management, and DevOps to deliver software across web, desktop, cloud, and IoT environments. The role is remote for candidates in the Seattle or Los Angeles metropolitan areas, with quarterly travel to Los Angeles.

Designs, deploys, and supports Cribl data models and log ingestion pipelines within an enterprise security environment. Supports SIEM, XDR, vulnerability management, DLP, endpoint security, Linux security sensors, and incident detection. Develops automation using Python and Bash, applies security controls, performs system hardening, contributes to threat mitigation, and maintains technical documentation. Collaborates with security architects to implement solutions aligned with business, regulatory, and risk requirements.

Build and launch production data systems and pipelines, provision dedicated AWS environments with infrastructure-as-code, and design connected data models with traceability and access controls. Own ambiguous engineering problems from concept through dependable production use, collaborate on architecture, and use AI and LLM-assisted tools extensively. The role requires independent work in a lean team and five days per week onsite in New York.

Leads customer-facing AI and data transformation engagements at Microsoft’s Dallas Innovation Hub. Designs scalable cloud, analytics, governance, security, and AI architectures; conducts discovery, envisioning, architecture sessions, and rapid prototyping. Guides strategic transformation for targeted accounts, facilitates cross-functional collaboration, advises on Microsoft data and AI technologies, and connects technical solutions to sales opportunities. The role is fully onsite and requires extensive technical pre-sales or consulting experience.

Lead the Ads Signals & Measurement data engineering team across conversion and attribution, measurement foundations, audience onboarding, and identity. Set cross-organizational technical direction, resolve scalable data architecture decisions, mentor engineers, and partner on platform-wide initiatives. The role requires expertise in modern data stacks, advertising technology data flows, privacy and governance, distributed systems, and emerging AI technologies.

Build and optimize marketing data platforms, applications, pipelines, algorithms, and tools. Analyze complex datasets using cloud technologies to support marketing optimization and business objectives. Develop reliable batch and streaming ETL/ELT pipelines, integrate data sources through APIs, and collaborate with engineering and marketing science teams to improve processes and discover new data sources.

Build and operate Python backend services, REST APIs, clinical data models, and batch or event-driven pipelines. Work with FHIR and HL7 healthcare data to support reliable integrations, reporting, analytics, and AI workflows. Establish data quality, validation, governance, lineage, monitoring, and auditability practices. Lead architectural discussions, review implementations, mentor engineers, and collaborate with clinical, product, analytics, and AI teams.

Design, build, and maintain scalable data platforms and ETL/ELT pipelines using Databricks/Spark and AWS. Develop backend data services in C#/.NET, ensure data quality and performance, leverage AI-assisted coding tools, collaborate with cross-functional teams, lead technical design decisions, and mentor engineers.

Develop and optimize large-scale data systems, ETL pipelines, storage, entity-resolution products, and data automation infrastructure. Build and integrate ingestion and processing pipelines using AWS, Airflow, Spark, PySpark, and EMR. Create testing and monitoring components, develop analytical tools, support data governance and quality, collaborate with data science teams, and document technical solutions.

Lead the modernization of Ampacity’s data platform by designing and implementing an Azure and Databricks lakehouse. Responsibilities include migrating Azure Data Factory pipelines, developing Delta Lake architectures, building SQL and Python transformations, establishing engineering standards, monitoring data quality, leading technical projects, mentoring engineers, and supporting team growth.

Own and evolve end-to-end data pipeline architecture across ingestion, transformation, modeling, and serving. Lead platform improvements for cost efficiency, reliability, access control, observability, orchestration, CI/CD, and developer experience. Drive complex cross-team initiatives, resolve production issues, influence architectural decisions, mentor engineers, and build automation incorporating AI into data engineering workflows.

Develop and maintain interactive BI dashboards, reports, data models, and pipelines using Power BI, Tableau, and Amazon QuickSight. Translate stakeholder requirements into visualization solutions, perform ETL and administrative tasks, manage data connections and governance, and provide user support and training. Create documentation and collaborate with federal stakeholders to deliver real-time organizational insights.

Designs, develops, and tests scalable enterprise data management solutions, including acquisition, integration, and transformation pipelines. Builds data structures and infrastructure across cloud and edge environments using Azure, Databricks, SAP Data Services, and DevOps practices. Manages continuous integration and deployment pipelines, supports containerized deployments, and collaborates with technical leaders, analysts, product owners, and stakeholders to define requirements and deliver data-driven solutions.

Lead architecture and development of Beacon’s backend data platform, including PostgreSQL data models, Kafka event pipelines, GraphQL APIs, clinical data access controls, and warehouse snapshot pipelines. Design complex systems, tune queries, operate production services, debug cross-system issues, write RFCs, mentor engineers, improve tooling and documentation, and collaborate with scientific, clinical, product, and engineering stakeholders.

Leads Knowledge Management, operational intelligence, service reliability, continuous improvement, and data governance across MedTech R&D applications. Develops dashboards, analyzes service and support data, improves CMDB quality, identifies reliability risks and automation opportunities, and supports AI-ready knowledge foundations. Partners with product, operations, reliability, support, and vendor teams to improve service quality, self-service adoption, issue resolution, operational efficiency, and application portfolio governance.

Build full-stack tools, backend services, APIs, dashboards, and data workflows for assessing and improving AI training data and evaluations. Partner with quality and research teams to inspect agent trajectories, validate graders, measure quality, investigate workflow issues, and turn internal prototypes into reliable production platform capabilities.

Designs and implements data models, schemas, and ETL/ELT pipelines supporting analytics, reporting, and machine learning. Optimizes query performance, partitioning, and clustering; establishes data quality, governance, and security standards; integrates data with BI and machine learning tools; documents workflows; and mentors junior engineers. Collaborates with data scientists, analysts, and product owners to architect cloud-based analytical infrastructure and data marts.

Leads 24/7 operations, maintenance, troubleshooting, and emergency response for data center infrastructure. Maintains electrical, mechanical, fire/life safety, controls, security, and building systems, including generators, UPS equipment, switchgear, chillers, CRAC units, BMS, and CMMS. Interprets construction documents, coordinates drawing updates, performs repairs, supports continuous facility resilience, and communicates with internal and external customers. The role requires on-site availability in Charlotte, North Carolina, applicable operating licenses, Universal CFC certification, and authorization to work without sponsorship.

Design and lead scalable data architecture and AI pipelines that transform disparate and unstructured data into production-ready organizational intelligence. Build batch and streaming integrations with Snowflake, optimize databases through sharding, replication, indexing, and normalization, and support relational, vector, graph, and document data models. Collaborate with data scientists and analysts, develop enabling frameworks, document architecture, and guide production-ready AI infrastructure across AWS and enterprise platforms.

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.