Top Data Engineer Jobs in Portugal

The Software Engineer will develop and manage data platforms for CoreWeave, focusing on performance, security, and scalability while facilitating data access and compliance with regulations.

Design and implement data platforms, manage data infrastructure, develop streaming architectures, improve performance, and ensure data compliance.

As a Senior Data Engineer, you will optimize the data platform, build efficient pipelines, democratize data access, and drive strategic infrastructure decisions to enhance data initiatives at January.

The Staff Data Engineer will lead design and implementation of analytics platforms and data products, collaborate cross-functionally, mentor engineers, and drive best practices at Upside.

The Senior Data Engineer will design and build scalable ELT/ETL pipelines, improve data quality, and collaborate with teams to ensure accurate data delivery and operational excellence within Cedar's data platform.

Lead design and optimization of high-throughput data ingestion pipelines and Python-based microservices. Improve pipeline performance, reliability, and observability across distributed systems, define unified ingestion architectures, work with Snowflake for analytics, mentor engineers, and collaborate cross-functionally to ensure scalable, fault-tolerant data platforms.

The Lead Data Engineer designs and develops technical solutions, collaborates with Agile teams, and utilizes big data technologies, cloud computing, and full-stack development to drive digital transformation at Capital One.

Lead and mentor a data engineering team to design, develop, test, and support cloud-based big data and streaming solutions. Build full-stack data pipelines using Java/Scala/Python, RDBMS/NoSQL, Redshift/Snowflake, and cloud platforms. Collaborate with product managers, perform unit tests and code reviews, and promote engineering best practices and tech community engagement.

Design, build, and maintain production-grade ETL/ELT pipelines and data models using dbt, Spark, and cloud platforms. Manage ingestion, data quality, observability, semantic layers, and BI outputs. Collaborate with analysts and data scientists to deliver governed, high-quality data products and implement DataOps and CI/CD practices.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

New-graduate Data Scientist role building and deploying ML and GenAI systems at scale for cybersecurity. Responsibilities include model development, fine-tuning LLMs, embedding-based search, production-ready code, automated tests, architecture reviews, and cross-functional collaboration to deliver AI-powered security capabilities.

Lead architecture and standards for CoreWeave's enterprise data ecosystem: design lakehouse/streamhouse architectures, modeling and semantic layers, governance, data quality, lineage, observability, and reusable data products. Drive cross-domain solutions, resolve performance and scalability constraints, evaluate core data technologies, conduct architecture reviews, and mentor senior engineers.

Design, build, and operate instrumentation, DAQ, and automated test control systems for spacecraft testing. Develop test automation (LabVIEW, Python, MATLAB), commission and calibrate sensors, troubleshoot hardware/software integration, perform post-test data analysis, and maintain data management and requirements traceability in hazardous test environments.

Design, develop, and maintain enterprise data pipelines, ETL/ELT workflows, and data management processes in Markit EDM. Integrate market, reference, and transactional data from vendors and APIs, implement data quality checks and reconciliations, support reporting and downstream integrations, troubleshoot production issues, and mentor junior engineers within an agile squad-based team.

The role involves developing and maintaining data workflows for research teams, managing scientific applications and data governance while collaborating with scientists and vendors to deliver scalable informatics solutions.

The Senior Cloud Data Engineer will architect cloud solutions, design data pipelines, ensure data governance, troubleshoot performance issues, and mentor team members while applying best practices in data engineering.

We are seeking a Data Engineer to design, build and optimize scalable data pipelines. Strong experience in Databricks, PySpark, and data warehouse concepts is required.

Lead data architecture and platform strategy for IHFM products. Solve complex data engineering problems at device-data scale. Define standards for ingestion, modeling, governance, lineage, validation, quality, SLAs, and traceable pipelines. Influence roadmap with product and engineering leadership.

Build and maintain ETL pipelines with Alteryx Server, support data warehouse integration and migrations, perform data cleansing/transformation, optimize SQL/Python pipelines, and produce Power BI reports as needed while collaborating with stakeholders.

Design, build, and maintain cloud data pipelines and data architecture using AWS/Azure/GCP. Advise clients on cloud data strategies, collaborate with stakeholders, and deliver production-ready data products.

Design, build, and maintain cloud data pipelines and data architecture on AWS, Azure, or GCP. Advise clients on cloud data strategies, collaborate with stakeholders, implement production data systems, and articulate architectural tradeoffs.

As a Data Engineer at Booz Allen, you'll manage data engineering activities, develop scalable platforms, and work with multidisciplinary teams to extract meaningful insights from big data.

Build and maintain ingestion pipelines for heterogeneous healthcare data (TPA feeds, claims, eligibility, enrollment). Design dbt models and orchestration (Dagster/Airflow), implement data quality monitoring and observability, and partner with data science to produce and maintain feature pipelines and feedback loops.

Design, build, and maintain secure, scalable data pipelines and platforms (including Palantir Foundry/Gotham) for mission-driven clients in classified or restricted environments. Guide cross-functional teams, communicate architecture decisions, implement secure analytics ecosystems, and support AI/ML integration and DevSecOps practices under constrained mission conditions.

Build and maintain enterprise data pipelines, warehouses and lakes using Java, Spark and Kafka. Lead a development team, ensure data quality, observability, security and regulatory compliance (FINRA/SEC). Implement scalable APIs on Kubernetes, authentication with OAuth2/JWT, and testing via JUnit/Mockito. Collaborate with data scientists to deploy ML models and drive data governance.