Top Data Engineer Jobs in Portugal

Design, build, test, deploy, and monitor batch and streaming data pipelines and ETL processes. Evaluate and adopt data technologies (including Adobe Experience Platform and CDPs), collaborate with data scientists, architects, and business partners to ingest and prepare large semi-structured/unstructured datasets for ML training, model execution, and search analytics, and implement automation, documentation, and tooling for scalable analytic data systems.

Run technical discovery with customers, design and build end-to-end data integrations into Spiral, implement ingestion code and infra-as-code, operate orchestration and monitoring, reconcile and backfill data, and own post-go-live schema and feed changes while collaborating with Sales and CX teams.

The role involves developing software solutions in collaboration with cross-functional teams, utilizing cloud technologies and agile methodologies, while optimizing processes and data analytics.

Design and implement scalable data engineering, ETL, data lake and reporting solutions. Build data infrastructure and pipelines using Oracle, Snowflake, Airflow, Informatica and AWS. Collaborate with product owners and analysts, ensure alignment with enterprise data strategy, perform data modeling, reconciliation, automation (Control‑M), and coach team members while participating in SDLC and DevSecOps practices.

Design, develop, test, deploy, and maintain scalable ETL and BI/data warehouse solutions in cloud/on-prem environments. Build CI/CD pipelines, automation, test frameworks, and data quality processes. Collaborate with analysts and engineers in Agile teams to deliver reliable, observable, enterprise-grade data platforms.

Design, build, and operate enterprise-scale data pipelines and platforms (ETL/ELT) using Palantir Foundry and Databricks. Parse and process structured and unstructured data, develop scripts to convert data, mentor cross-functional teams, and monitor/scale data solutions for mission-driven analytics.

Lead architecture and implementation of a large-scale analytics stack: design foundational pipelines, establish modeling/orchestration standards, integrate AI-assisted engineering tools, translate business questions into version-controlled data models, partner with stakeholders to define metrics and data contracts, migrate logic into maintainable pipelines, and optimize cloud warehouse performance for scale.

Designs, proposes, and codes complex data and automation solutions on AWS; leads problem solving, provides technical guidance, and applies IaC and modern tooling to align software with business strategy. Works with AWS data/ML services and mentors teams to deliver reliable production systems.

Build and optimize backend data pipelines and calculations for 7M+ securities using Python/Django. Implement Airflow pipelines, pandas/Celery-based async calculations, database query tuning, caching, scalable data models, incident investigation, code reviews, and cross-team collaboration to ensure timely, accurate financial data.

Design, harden, and scale Snowflake and AWS data platforms, build dimensional data models and resilient Airflow pipelines, optimize complex SQL, develop dbt semantic layers, deploy ML models in AWS, integrate AI/LLMs into workflows, and build data APIs (FastAPI/Flask) to enable enterprise analytics and operational ROI.

Design and implement data cleaning, preprocessing, integration, and quality checks. Develop dashboards and complex visualizations (Tableau/Power BI). Apply AI/ML techniques for unstructured data analysis and provide data engineering support for visualization and analytics.

Lead and mentor engineering teams to design, build, test, and support cloud-based data solutions. Work with big data, streaming, and data warehousing technologies, collaborate with product managers, and ensure performant, well-tested code and architectures.

Lead and mentor a team of data engineers to design, develop, test, implement, and support cloud-based data platforms and full-stack solutions. Build distributed, real-time, and batch data systems using Java/Scala/Python, big data tools (Spark, Hadoop, Kafka), NoSQL and RDBMS, and data warehouses (Redshift, Snowflake). Collaborate with Agile teams, perform unit tests and code reviews, and drive technology experimentation and transformation.

Build and maintain production data pipelines and infrastructure to prepare multimodal conversational, voice, sensor, and telemetry data for ML training and evaluation. Implement dataset versioning, lineage, quality monitoring, and tooling to enable reproducible, discoverable datasets and cost/performance-optimized large-scale processing while enforcing data governance and privacy.

The role involves designing and building scalable data platforms, migrating data to the cloud, and implementing CI/CD practices while collaborating with cross-functional teams.

The role involves managing data infrastructure, building data pipelines, providing analytics to inform business decisions, and shaping AI workflows in the organization.

The role involves structuring and ingesting customer data, setting up ETL pipelines, and providing solutions for data export and import.

As an AWS Data Engineer, you will develop data pipelines, create data models, troubleshoot issues, and collaborate with teams while utilizing tools like PySpark and SQL.

Solutions Engineers at Vori configure grocery platforms for retailers, handling data integration and customer interactions to solve complex problems.

The Data Engineer will design and implement scalable data platforms, build data pipelines, collaborate with teams to ensure data quality, and streamline processes using AWS services and big data technologies.

The Gen AI Data Engineer will design and build distributed data systems, develop data pipelines, manage data infrastructure, and integrate technologies for real-time and batch processing, contributing to scalable analytics solutions.

As a Business Intelligence/Data Engineer, you will analyze data structures, implement data warehousing solutions, and design data visualizations while working with AI/ML services in cloud environments.

The Principal Data Engineer will lead data architecture initiatives, design scalable data systems, and oversee data standards across teams while ensuring high-quality data infrastructure and guiding engineering teams.

The IT Controls Data Engineer will create and maintain data pipelines and automated evidence workflows for IT controls, ensuring compliance and audit readiness.

Design, build, and deploy scalable data pipelines and validation for government production environments. Establish and maintain schemas, optimize SQL, handle messy/disparate data sources, work with large (100GB+) workflows, use Databricks/Spark/Python, and support ML/predictive solutions while mentoring teammates and engaging with clients. Active Secret Clearance required.