Top Data Engineer Jobs in Portugal

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.

Designs and scales enterprise backend services, data platforms, pipelines, and distributed processing solutions. Leads architecture, graph-based data initiatives, Snowflake implementations, engineering standards, code reviews, CI/CD, testing, and AI-assisted development. Partners with technical and business stakeholders, ensures security and regulatory compliance, optimizes platform performance, and mentors engineers.

Design, build, deploy, and support production data pipelines and enterprise data solutions in Databricks and GCP. Develop data models and layered architectures, ensure data quality, security, and governance, integrate multiple sources, and support analytics, AI/ML, reporting, and operational decision-making while collaborating with technical teams and federal stakeholders.

Leads the architecture, development, deployment, and operation of scalable production data pipelines. Defines data strategy, integrates enterprise data solutions, ensures governance and performance, communicates with executives, and mentors engineers. The role provides technical leadership in a growing practice and requires expertise across cloud platforms, orchestration, ETL/ELT, lakehouse architectures, and regulated-industry data environments.

Develops advanced data engineering and visual analytics applications for structured and semi-structured data. Designs enterprise database systems, builds large relational databases, develops and optimizes data pipelines, integrates systems with existing data warehouses, and improves system performance. Requires Java, AWS, ETL, Spark, Scala, SQL, PostgreSQL, NiFi, Informatica, and Linux experience, along with an active Top Secret/SCI-eligible clearance.

Build and oversee reliable ETL/ELT pipelines and data products that transform complex customer data into trusted analyses, visualizations, quality reports, and AI-powered insights. Responsibilities include data exploration, quality control, anomaly detection, AI/ML output evaluation, customer collaboration, documentation, and improving data-cleaning and analytics tools. The role requires cross-functional work in an Agile environment focused on security, data integrity, and clear communication.

Architect and maintain secure, scalable data platform infrastructure and resilient batch and streaming pipelines. Build infrastructure using Terraform and Helm, deploy cloud data services, optimize schemas and database performance, and implement monitoring and alerting. Partner with application teams to resolve data issues, establish governance practices, and support MLOps through model versioning, containerization, and deployment.

Build and maintain ETL/ELT pipelines, explore and clean complex customer data, and deliver trusted analytics products, reports, visualizations, and AI-powered data capabilities. Partner with customers and internal teams to define data requirements, investigate discrepancies, validate AI/ML outputs, implement quality controls, and improve data tooling through automation. Translate complex findings and workflows into clear narratives and repeatable processes.

Architect and maintain secure cloud data infrastructure, scalable schemas, and resilient batch and streaming pipelines. Deploy data platforms using Terraform, Helm, CI/CD, and infrastructure-as-code practices. Build monitoring and alerting for data health, system performance, and container observability. Troubleshoot application workflows, database queries, and pipeline logic while advancing data governance. Support MLOps through AI model versioning, containerization, and deployment.

Monitors and maintains critical data center systems, including mechanical, electrical, cooling, generator, fire suppression, and UPS equipment. Performs inspections, preventive maintenance, troubleshooting, installations, work order management, documentation, inventory tracking, and incident response. The role follows safety and regulatory procedures, coordinates with vendors and contractors, supports equipment upgrades, and works scheduled shifts, holidays, and rotating on-call coverage in an on-site environment.

Support data centre operations through installation, migration, maintenance, troubleshooting, break-fix, and decommissioning of compute, networking, storage, and high-density AI infrastructure. Perform smart hands support, cabling, site surveys, documentation, safety procedures, and on-call incident response while collaborating with engineering, project management, customers, and vendors to maintain uptime and service levels.

Designs, develops, and maintains IBM Planning Analytics and TM1 models, cubes, applications, rules, feeders, and TurboIntegrator processes for financial planning, forecasting, reporting, and actuarial modeling. Builds data ingestion, transformation, quality, masking, and curation processes; supports SQL development, security, performance monitoring, and critical data pipelines. Partners with finance and actuarial stakeholders, provides operational support, develops scalable tested code, and mentors team members.

Designs, builds, and operates large-scale Hadoop-based data pipelines and analytics platforms. Responsibilities include ingesting, transforming, and analyzing structured and unstructured data; developing Spark applications; managing streaming workflows; working with relational and NoSQL stores; orchestrating pipelines; troubleshooting distributed systems; and supporting reliable, scalable production data platforms.