Top Data Engineer Jobs in Portugal

Design, optimize, and operate large-scale data pipelines focused on performance and scalability. Support ML workflows including feature extraction, model training, and real-time inference. Build solutions using Python, SQL, AWS data services and Apache Spark, and train/deploy models with SageMaker, TensorFlow, or PyTorch in a fast-paced remote environment.

Design, build, and maintain reliable ELT/ETL pipelines and Snowflake data models using dbt, Dagster (or Airflow/Prefect) and Python. Ensure data quality, CI/CD deployment, documentation, stakeholder collaboration, and AI-ready data layers to support analytics and Snowflake Cortex use cases.

Responsible for building data models, developing ELT pipelines, implementing data quality checks, and utilizing best practices in data engineering and healthcare analytics.

Design, build, and maintain scalable data pipelines and architecture to support analytics and applications. Develop datasets and analytics tools, automate data workflows, ensure security/privacy of healthcare data, troubleshoot data issues, and partner with Product, Engineering, and business stakeholders to deliver data solutions.

Design, develop, and maintain databases and scalable data pipelines. Build stored procedures, triggers, and ETL processes; perform testing, tuning, security, and data quality work. Collaborate with developers and stakeholders, document architecture, review code, and support reporting and integrations to enable restaurant and customer-facing systems.

Design, build, deploy, and support high-performance data pipelines on GCP. Collaborate with business, IT, analysts, and data science teams to capture requirements, ensure data quality and lineage, optimize pipeline performance, document designs, and troubleshoot operational issues.

Design, build, and maintain ETL pipelines, databases, and data models to process healthcare claims and related data. Ensure data quality, analyze claims data for trends, and produce reports and visualizations for nontechnical stakeholders. Collaborate with policy and analytics teams to translate requirements into data solutions and improve data infrastructure and analytics capabilities.

Design and build scalable backend services and data ingestion pipelines to process and enrich data (including LLM enrichment). Perform data modeling, mapping, and large-scale file manipulation while collaborating in an Agile team to deliver reusable APIs, optimize performance, and improve processes.

Build and maintain Power BI reporting for FP&A: extract and transform data (Bronze/Silver), semantic modeling and dashboards (Gold), ensure accuracy, security, performance, and manage Power BI Service access and role-level security.

Design, build, and own Sardine's internal data platform and billing infrastructure. Implement and maintain ETL/ELT pipelines, warehouse partitioning, access controls, and data governance. Partner with stakeholders to define KPIs, produce dashboards, and ensure data quality for executive, GTM, product, and finance teams.

As an AI Data Engineer, you will build and maintain data pipelines and AI models to enhance GTM strategies, improving decision-making and operational efficiency.

The Data Engineer will design and implement data ecosystems, build data pipelines, and ensure data quality while collaborating with stakeholders and utilizing AWS services.

Design, build, and maintain batch and streaming data pipelines; ingest, transform, and optimize data for analytics and BI; ensure data quality, reliability, and performance; implement monitoring/alerting; support MLOps and analytics workloads; collaborate with data scientists and BI teams; document AI systems and RAG/Cortex-based solutions.

Lead hands-on data engineering and architecture for a classified on-prem Analytics Core: build ETL/ELT pipelines, clean and model 30 years of multi-modal and geospatial data, integrate ESRI spatial data, establish AI/ML feature standards, enforce DoD-aligned governance, and mentor transitioning staff to operationalize the solution.

Design, build, deploy, and support data integration and ETL pipelines on a Spark/Databricks and AWS-based platform. Lead requirements gathering, author technical designs and test plans, implement BI/analytics solutions, follow DevOps and agile practices, and improve integration architecture and operational procedures.

Design, build, operationalize, and maintain enterprise-scale data applications and scalable ETL/ELT pipelines. Develop and troubleshoot Palantir Foundry transformations, ontology objects, and logs. Collaborate with cross-functional teams to convert structured and unstructured data for analytics, monitoring, and platform operations.

Onsite Python data engineer supporting SOCOM in a classified SCIF. Build and maintain data pipelines, work with relational databases and SQL, develop on Mac/Windows/Linux, collaborate in agile teams, and support mission-focused data and analytics solutions.

Design, build, and maintain ETL/ELT data pipelines to ingest, transform, harmonize, and validate complex biomedical datasets. Collaborate with researchers and engineers to create analysis-ready, governed data products, dashboards, and APIs. Ensure data quality, lineage, security, documentation, and scalability while troubleshooting pipeline issues and contributing to platform modernization.

Design, build, and operationalize scalable AI/ML infrastructure and data pipelines. Implement model lifecycle management (MCP), integrate agent frameworks (e.g., LangChain), manage vector DBs and feature stores, enable HITL workflows, maintain data architectures, mentor junior engineers, and present work internally and externally.

Build and maintain software integrations and backend services to collect, normalize, and expose CPU and storage infrastructure data from heterogeneous sources. Design ingestion pipelines, data models, reconciliation and validation mechanisms, and interfaces to support analytics, planning, and operations. Partner with infrastructure teams to ensure reliability, observability, and scalability of data integrations.

Designs, builds, and maintains secure cloud data pipelines and centralized repositories; publishes curated datasets; develops WPS AI agents; produces dashboards and visualizations for senior military leadership; supports NATO and annual statutory reporting and prepares technical briefings and deliverables.

Design, develop, and maintain SSRS reports and Power BI dashboards; perform data modeling and DAX calculations; support ETL (SSIS) and validate data across EMR/billing/CRM systems; gather and translate stakeholder requirements; liaise with offshore teams; perform testing, documentation, and ensure HIPAA/PHI compliance and data governance.

Lead technical strategy, architecture, and modernization of enterprise master data and data lakehouse platforms. Design and implement large-scale data pipelines, databases, and distributed systems using Python, Spark, Redshift, Iceberg and AWS services. Ensure performance, reliability, governance, CI/CD, and AI-enabled engineering practices while mentoring senior engineers and aligning cross-functional stakeholders.

Design, build, and maintain enterprise data warehouse and medallion-layer dbt Core models. Integrate MDM workflows, develop scalable pipelines using Microsoft Fabric/Azure Data Factory, optimize Snowflake performance, ensure data quality, support CI/CD and monitoring, troubleshoot production issues, and collaborate with cross-functional stakeholders to deliver analytics-ready datasets.

Design, develop, and support the Data Warehouse and reporting systems. Build and optimize SSRS reports, Power BI dashboards, and SQL ETL/queries. Ensure data accuracy, maintain documentation, and mentor team members while collaborating with business units to translate requirements into scalable data solutions.