Top Data Engineer Jobs in Portugal

Analyze contact center and customer data to identify trends and KPIs, build AI-powered automation and optimization solutions, create dashboards and internal tools, process call transcripts and feedback to drive agent coaching and quality improvements, and partner with stakeholders to implement scalable AI/analytics solutions and executive updates.

Build and scale the company's data infrastructure: design ingestion paths, event models, schema-flexible data models, change capture, query performance, freshness guarantees, and analytics serving for customer-facing dashboards and evaluation pipelines.

Design, develop, configure, and support Customer MDM and Informatica Product 360 solutions, including data models, workflows, integrations, data quality, governance, and production support across enterprise systems. Collaborate with stakeholders throughout the SDLC to implement MDM/PIM processes, troubleshoot incidents, and maintain documentation and release activities.

Design and build data models, automated pipelines, and dashboards to support Lunar program planning and technical performance. Partner with stakeholders to gather requirements, create visualizations and metrics for leadership, lead cross-functional data modeling efforts, and establish data quality and documentation standards to scale analytics across programs.

Design and maintain scalable data pipelines, ensuring accuracy and reliability. Collaborate with engineers to optimize data systems and enforce best practices.

As a Data Engineer, you will build and optimize data pipelines, ensuring accurate data delivery that informs pricing and market analytics at Alt.

Design and maintain pipelines and tooling to ingest, validate, model, and serve multi-modal driving data for ML training, evaluation, and debugging. Collaborate with ML, vehicle software, curation, and fleet teams to scale the data stack and make datasets discoverable and queryable.

The Data Engineer will develop and implement software solutions for law enforcement, focusing on data management, system optimization, and effective communication with clients.

The Data Engineer will develop data and software solutions for law enforcement, create reports, and manage data sources. Responsibilities include collaborating with teams to analyze data, communicate with clients, and ensure high-performance analytics tools.

Build, maintain, and support scalable data systems and pipelines. Ingest, clean, structure, and enrich data from multiple sources. Ensure data quality, security, and governance. Collaborate with analysts and data scientists to design solutions, deploy and optimize pipelines, and diagnose and resolve data issues to support analytics and reporting.

Design and maintain scalable batch and real-time data pipelines, build governed data models for a CDP, ensure data quality and security, support identity resolution and customer 360, mentor junior engineers, and collaborate with analytics and business stakeholders to deliver actionable customer insights.

As an Azure Data Platform Consultant, you will deliver data solutions using Azure and Fabric, engage with clients, design solutions, and optimize data platforms.

Responsible for building and operating scalable lakehouse data pipelines, optimizing data flows, and delivering analytics-ready data products using Azure Databricks technologies.

Design, build, and maintain scalable data pipelines and ETL processes in Azure (Synapse, Data Factory). Integrate data via APIs, ensure data quality/security, support analytics and Power BI reporting, collaborate with stakeholders, and manage work using Agile/Jira to support federal healthcare and VA initiatives.

Design, build, and maintain scalable data assets and pipelines for analytics and ML; validate and ingest diverse data sources; perform exploratory data analysis and data quality checks; collaborate with cross-functional teams and produce reproducible code and documentation.

Design, build, and optimize scalable data pipelines for large-scale structured and unstructured healthcare data to support ML and GenAI workloads. Implement ingestion, transformation, validation, orchestration, monitoring, and data foundations (feature pipelines, embeddings/vector stores). Collaborate with architects, data scientists, and DevOps to deploy and secure cloud-based pipelines while ensuring compliance with SOC 2, HIPAA, and GDPR. Mentor junior engineers and drive best practices in version control, metadata, reproducibility, performance tuning, and cost optimization.

The role involves engineering modern data platforms, focusing on data ingestion, transformation, and storage while utilizing Azure services and MS Fabric, supporting an investment management firm.

The Data Engineer will lead data lifecycle strategy, manage data acquisition and cleansing, and collaborate with teams to optimize data solutions and architecture.

Design, build, and maintain Python-based web applications and Azure data pipelines to support procurement and supply chain tools. Implement CI/CD, integrate REST APIs, author and optimize T-SQL/SQL Server queries, manage data ingestion/transformations, and deliver data for visualizations while ensuring code quality, security, and stakeholder collaboration.

Design, build, and optimize enterprise data foundations, ETL/ELT pipelines, data models, and migrations. Ensure data quality, governance, and secure integrations across financial, practice-management, CRM, and operational systems to support reporting, automation, and AI initiatives.

Own and evolve end-to-end data pipeline architecture across ingestion, transformation, modeling, and serving. Lead platform improvements (cost, compute efficiency, access control), CI/CD, monitoring, and incident response. Drive cross-team technical initiatives, mentor engineers, and integrate AI tooling to improve workflows while remaining hands-on building and debugging production pipelines.

Design, build, and operate high-volume data pipelines between Snowflake and Databricks using PySpark and dbt; orchestrate workflows with Airflow; administer Databricks and OpenShift environments; implement retrieval and ML systems (NER, XGBoost, Keras, forecasting); operationalize MLOps with MLflow; manage CI/CD, container builds, and OpenShift deployments; lead security/compliance assessments and remediation with SAST and vulnerability scanning.

Design, build, and operationalize Databricks-based cloud data lakehouse solutions. Develop dbt transformation pipelines, implement CI/CD with Azure DevOps, apply IaC (Terraform), optimize database performance, participate in code reviews, and lead delivery planning for a squad of data engineers in Agile ceremonies.

Design and build SOCOTEC's enterprise data platform: scalable Databricks/Spark/Delta Lake pipelines, data models, and MDM. Ingest from ERP/CRM, enable batch and near-real-time processing, ensure data governance, quality, lineage, and provide datasets for analytics and AI while driving architecture and observability.

Design and implement a scalable data platform and integration pipeline to ingest, normalize, and index enterprise data. Build connectors, ETL/streaming pipelines, and storage/indexing strategies to support semantic search and GenAI use cases. Partner with applied AI teams, make build-vs-buy decisions, and create reusable patterns to scale integrations.