Top Data Engineer Jobs in Lisbon

The Data Engineer role focuses on programming, data integration, and working within cloud environments while ensuring team collaboration and professional development.

As a Mid Data Engineer, you will design data tools, automate processes, and collaborate with clients to enhance their data needs.

The Data Engineer will design data pipelines and architecture, optimize machine learning models, and collaborate on data projects for international brands.

Design, build and maintain data integrations and pipelines on Databricks and Azure Data Factory. Cleanse and curate data, monitor batch jobs, engage stakeholders to translate requirements, document solutions, and support the cloud and legacy on-prem platforms while enabling self-serve reporting.

Build the companys first data stack and data products (internal analytics and customer-facing). Work across data engineering, devops, and software tasks; ship early features, improve developer experience, document proposals, and iterate based on feedback.

Design, build, and maintain data ingestion and transformation pipelines into Snowflake. Troubleshoot incidents, run backfills, validate data, write tested dbt models, migrate data from MSSQL/Oracle, monitor pipelines, and document solutions for team use.

Design, build, and scale ETL/ELT and real-time data pipelines for AI workloads (RAG, fine-tuning, batch inference). Transform unstructured data into vectorized formats, manage feature stores and vector databases, enforce data quality/governance, integrate event systems (Kafka), and collaborate with ML and engineering teams.

The Python Data Engineer will design and maintain scalable data pipelines for data-driven decision making, collaborating with cross-functional teams and ensuring data quality and compliance.

As a Data Engineer, you'll build and optimize data infrastructure, manage pipeline migrations, and implement data governance and monitoring tools that improve data quality and observability.

Design and implement data pipelines and solutions using Azure services, focusing on data modeling, transformation, and compliance in a collaborative environment.

As a Data Engineer, you will design, build, and maintain data pipelines for healthcare data and support AI initiatives within biopharma, ensuring scalability and integrity in data management.

As a Junior Data Engineer, you will design and maintain data architectures, process large data sets, and work with tools like Spark and AWS.

The Data Engineer will design and maintain data architectures, develop data pipelines, monitor data processing performance, and mentor junior team members.

The Senior Data Platform Engineer will develop and manage a large-scale data platform, oversee infrastructure performance, and mentor other team members.

Design, implement and maintain scalable data pipelines, storage, ETL and data warehousing on Azure. Manage data integration, architecture, security, governance and cloud-based services (Azure Databricks). Use scripting (Python) and data technologies (Spark, SQL/NoSQL) to support analytics and Power BI integration.

Lead foundational data-engineering work to validate and re-engineer pipelines for an anonymized, centralized credit data lake. Harmonize schemas across entities, build dbt models and tests, implement data-quality suites (Great Expectations), entity resolution, anonymization controls, optimize Spark/Glue jobs, orchestrate pipelines (Airflow/Step Functions), and produce documented, feature-ready datasets and runbooks for a regulated UK/Ireland lending environment.

Own end-to-end AI-automated data platform migration projects (1-4 concurrently): scope, plan, execute, and hand off. Act as primary customer contact, configure Datafold's Migration Agent, partner with engineering on execution, and help refine delivery playbooks.

The Senior Product Data Engineer will build, iterate, and launch data products, focusing on large-scale data processing and ETL/ELT pipelines, using various technologies and implementing AI features.

As a Data Engineer, you'll analyze user data and product performance, create dashboards, and utilize SQL and Python to derive insights for business strategies.

Design, build, and maintain scalable data pipelines and storage for fraud detection. Support fraud analytics, feature engineering, model integration and serving, pipeline monitoring, and documentation. Collaborate with data, product, and engineering teams to enable detection, reporting, and operationalisation of fraud models.

Design and maintain AWS-based data pipelines, processing vehicle data, implementing ETL/ELT infrastructure, and collaborating with stakeholders to deliver analytics-ready datasets.

Build and maintain Spark-based data pipelines for Veeva Link's next-gen data platform. Design, implement, and refactor features using JVM languages or Python, collaborate with data science to operate ML models, and ensure observability, monitoring, and quality across the data processing platform.

The Principal Data Engineer will improve data pipeline architecture, optimize data flows, and support data projects for various teams in the company.

As a Data Engineer, you will design and manage data pipelines, process diverse data types, and support stakeholders in technology decisions. You'll also improve pipeline performance and work on innovative projects to create intelligent data products for clients.

The Data Engineer designs big data architecture, optimizes machine learning models, collaborates on data projects, and builds data pipelines.