Top Data Engineer Jobs in Portugal

Lead the architecture, circuit design, integration, verification, tapeout, and silicon validation of high-speed ADCs, DACs, and analog front-ends for advanced mixed-signal SoCs. Drive architecture trade studies, calibration techniques, FinFET CMOS implementation, converter integration, simulation methodologies, and collaboration with RF, digital, systems, package, and verification teams. Provide technical leadership and mentorship to analog and mixed-signal engineers.

Leads the architecture, circuit design, integration, verification, tapeout, and silicon validation of high-speed ADCs, DACs, and analog front-ends for advanced mixed-signal SoCs. The role covers converter trade studies, FinFET CMOS circuit implementation, calibration, clocking, references, signal integrity, and DSP collaboration. It also provides technical leadership, establishes design methodologies, and mentors analog and mixed-signal engineers.

As a Data Engineer, you design and optimize data pipelines, warehouses, and lakes, collaborating with analysts and engineers to support BI and ML initiatives.

The Data Engineer II designs, develops, and maintains data integration and analytics solutions, ensuring data quality and accessibility for business stakeholders, while collaborating with teams to meet business needs.

The Data Engineer will design, develop, and implement data solutions, ensuring data integrity and availability, collaborating with stakeholders to meet business analytics needs.

Build and maintain scalable web crawlers to extract, validate, and structure product data from eCommerce sites. Use AI-driven techniques, browser automation, proxies, and APIs to handle dynamic content and anti-bot measures. Monitor performance, clean large datasets, collaborate with Product/Engineering/Data teams, and continuously improve crawling frameworks and automation.

Design, build, test, and maintain data architectures, database systems, and pipelines using GCP and BigQuery. Optimize data retrieval, automate processes, redesign infrastructure for scalability, collaborate with stakeholders, and deliver analytics tools that provide actionable business insights.

Designs and delivers scalable, low-latency streaming data pipelines using Apache Flink, Confluent Kafka, and Apache Iceberg. Modernizes batch and RDBMS workflows into event-driven architectures, builds lakehouse data structures, ensures data quality, optimizes streaming performance, and integrates ITSM and enterprise systems. The role also leads testing, documentation, delivery lifecycle activities, stakeholder collaboration, CI/CD, operational monitoring, and mentoring of data engineers.

The Data Engineer is responsible for building and maintaining data pipelines, ensuring data quality and reliability, and collaborating with various teams on data needs. This involves working with AWS tools and programming in Python and SQL to support analytics and infrastructure.

Design, build, and optimize end-to-end data pipelines and dataflows, integrate with AWS, maintain schemas/data dictionaries, provide Tier 3 support, collaborate with stakeholders and product teams, document architectures, and support off-hours deployments. Ensure data governance, scalability, and production readiness while working primarily on-site in a cleared defense environment.

As an AWS Data Engineer, collaborate with teams to build data products, write efficient PySpark and SQL queries, and manage project deliveries.

The role involves designing and operating an AIOps platform, ensuring reliability, scalability, and efficient automation for AI solutions with collaboration from data teams.

The role involves developing and maintaining the Enterprise Data Warehouse, optimizing queries, and supporting data analysis and business intelligence activities.

Build and consolidate data infrastructure for ML training: design automated ETL/ELT pipelines, implement DataOps practices (validation, monitoring, anomaly detection), integrate annotation workflows, manage dataset versioning and storage, and collaborate with ML engineers and operations to produce high-quality, reproducible training datasets.

The Data Engineer will design databases, develop ETL tools, optimize SQL, and work with cloud platforms while ensuring data performance for clients.

Design and build scalable cloud-native data pipelines and models to produce trusted, analysis-ready data. Ensure data quality, governance, and privacy controls, apply software engineering best practices, enable BI and AI/ML consumption, and collaborate with clients and cross-functional teams.

Design, develop, and manage scalable database systems, data pipelines, structures, and load routines primarily in AWS RDS for PostgreSQL and SQL environments. Support application teams through APIs, database optimization, data processing, and reporting tools such as Power BI. Collaborate with technical and non-technical stakeholders in an Agile setting. The role requires U.S. citizenship and an active TS/SCI with Polygraph clearance.

Develop and deploy high-performance, highly available Java server-side applications and evolve existing systems into large-scale service architectures. Apply object-oriented design, architectural patterns, distributed computing frameworks, serialization technologies, REST, SQL, unit testing, mocking, and build tools. Work with Hadoop ecosystem technologies and learn emerging big data analytics platforms.

Design, develop, and optimize scalable batch and real-time data pipelines on GCP. Implement Medallion Architecture, build Python and PySpark transformations, optimize BigQuery and SQL workloads, deploy Dataflow pipelines, and orchestrate workflows with Cloud Composer and Airflow. Manage GCS storage, CI/CD, version control, IAM, data governance, security, reliability, scalability, and cost efficiency across enterprise data platforms.

Develop and maintain cloud-based data platforms supporting data science applications and services. Responsibilities include cloud infrastructure administration, system operations, monitoring, troubleshooting, security accreditation support, account and credential management, repository maintenance, and backup and restoration. The role also involves deploying environments, automating infrastructure and application delivery, supporting containers and orchestration, and collaborating with software development teams in controlled security environments.

Provides technical support for data services by troubleshooting access, quality, and availability issues; resolving customer tickets; documenting solutions; training users; monitoring service health; tracking support metrics; coordinating with technical teams; and supporting change management, escalation procedures, proactive monitoring, and new platform features.

Provides technical leadership for enterprise data platform engineering. Designs and implements ETL, ELT, streaming ingestion, data models, cloud data lakes and warehouses, monitoring, data quality, governance, testing, version control, and CI/CD practices. Leads AWS, Snowflake, and dbt implementations while integrating disparate data sources for analysts and data scientists. Partners with business stakeholders to align data products with organizational strategy and enables self-service analytics and automation.

The Staff Data Engineer will lead the architecture and scalability of H1's healthcare data processing systems, ensuring efficient entity resolution and big data operations. Responsibilities include design and optimization of distributed Spark pipelines, team leadership, and collaboration with AI/ML teams to enhance data processing capabilities.

Implements and supports security data ingestion pipelines across applications, cloud services, infrastructure, security tools, and business systems. Develops transformations, parsing, normalization, enrichment, masking, validation, and delivery workflows. Troubleshoots data quality and pipeline issues, documents architectures and data flows, coordinates with client stakeholders, and supports SIEM, detection, investigation, observability, and automation use cases. Requires data engineering experience, scripting, query languages, integration knowledge, and strong client communication.

The Senior Research Engineer will curate large datasets, automate data pipelines, optimize queries, and support data-driven research impacting business outcomes.