Top Data Engineer Jobs in Lisbon

The Data Engineer will create and manage automated data pipelines, optimize data architecture, lead stakeholder sessions, and guide junior engineers.

The Senior Big Data Engineer will deliver a global big data platform, produce big datasets, write high-quality code, build and maintain automation test suites, and work in Agile development teams.

The Data Integration Engineer will design and maintain integrations between client ERP systems and Prophix, focusing on data processing, API development, and collaboration with cross-functional teams.

The Data Engineer will design and maintain data pipelines, optimize ETL processes, ensure data quality, and collaborate in an agile environment.

The Junior Data Engineer will analyze data, design experiments, build a marketing data stack, and collaborate with teams to improve data access and insights.

Landskill is seeking a Big Data Engineer with experience in big data tools and programming. Duties include data modeling, ETL, and integration, with a focus on personal and professional development.

The Senior Data Engineer will build core infrastructure software for data platforms, mentor engineers, and ensure data access and performance across systems.

Design and maintain data pipelines, collaborate with stakeholders, ensure data quality, deploy infrastructure as code, and optimize reporting solutions.

Join Bitsight as a Senior Software Engineer to build and maintain large-scale data pipelines, enhance cybersecurity insights, and collaborate with cross-functional teams.

The Senior Data Engineer will design and maintain scalable data pipelines, ensure data quality, and develop backend services to support WalletConnect's payments infrastructure and analytics.

Design, build and maintain scalable batch and streaming data pipelines and architectures. Monitor production pipelines, perform root-cause analysis, collaborate with data scientists and product teams, mentor junior engineers, and drive technical improvements to support analytics and ML workloads.

Design and build reliable, performant data pipelines for large payment datasets. Own end-to-end data flows, drive data quality, implement transformations (dbt), operate on StarRocks and Flink/Spark in cloud (AWS/GCP), collaborate cross-functionally, establish engineering standards, mentor engineers, and shape CI/CD and incident practices.

Lead the migration of workloads to Iceberg, build batch and streaming pipelines using Spark and Flink, and collaborate on data API integrations.

The role involves designing and managing data solutions using Databricks and Azure, automating processes, optimizing pipelines, and collaborating with teams to deliver effective data workflows.

The role involves developing and supporting data processing pipelines, collaborating with ML Engineers, and improving infrastructure while mentoring team members.

The Senior Data Engineer will develop and maintain data pipelines, support data analysis, ensure architecture meets business needs, and communicate with stakeholders.

As a Staff Data Engineer, you'll design and implement data processing systems, build data pipelines, and architecture data infrastructure to provide actionable insights.

The role involves creating and automating infrastructure features for data platforms using Python, with a focus on distributed systems and collaboration within a global team.

The role involves automating OpenSearch operations by developing features in Python, collaborating with an international team, and providing expertise on data platforms.

As a Software Engineer on the data platform team, you'll automate data platform operations, write Python code, and collaborate on solutions within a distributed team.

As a Lead Data Engineer, you will manage and mentor junior data engineers, architect and deliver cloud-based data solutions, and ensure effective data governance while aligning with the company's data strategy.

Join Zencore as a Senior Data Engineer, leveraging Google Cloud expertise and technology strategies to assist clients with data and application modernization.

You will develop data pipelines, integrate APIs, prepare data for GenAI processing, and ensure code quality and scalability.

Design, build, and maintain a trusted semantic layer and reusable data models (dimensions, facts, metrics). Translate business logic into clear data specs, improve model reliability with testing and lineage, drive adoption across teams, standardize modelling conventions, and enable self-serve analytics for product, GTM, and finance stakeholders.

Design and build cloud-native, low-latency data and ML infrastructure; implement state-of-the-art research into backend services; write testable code; communicate results via papers/patents; collaborate with Product and Data Science.