Top Data Engineer Jobs in Portugal

As a Senior Controls Engineer, you will design, deploy, test, and maintain control systems, ensuring quality through collaboration with clients and team members.

Build and operate an AWS-native data lake and AI gateway. Implement and maintain lakehouse architecture (Iceberg) using Glue, Athena, and S3; manage infrastructure as code (Terraform); run reliable data pipelines; operate LLM gateway/Bedrock; enforce security, IAM, networking, and secrets controls; partner with IT and Security.

Design, develop, and maintain scalable ETL/ELT pipelines and Snowflake data models; optimize performance; ensure data quality and integrations with CRM/ERP/billing systems; collaborate with stakeholders and evolve a Snowflake/dbt cloud-native data platform.

Assist the data engineering team in building, testing, and documenting data pipelines and storage. Work with Python, SQL, and Git on time-sensitive tasks, execute unit tests, support senior engineers, and complete assigned projects (part-time, 20 hr/week).

Design, develop, maintain, and test data infrastructures and pipelines; optimize data flow and collection; collaborate with data science to integrate models; analyze IT environments; deliver data solutions for stakeholders and support project milestones.

Build and maintain high-throughput C++ recording systems and Python data services for vehicle sensor and telemetry data. Work on data transfer, ingestion, validation, format/versioning, indexing, compression, and efficient access for replay, analytics, and ML while operating under vehicle resource constraints and contributing to quality management.

Own and scale the usage-to-billing pipeline and real-time CRM ingestion, design the customer/commercial graph, work across front-end and backend ingest infrastructure, and mentor engineers while shaping system architecture and operational reliability.

Design, build, and maintain backend systems and data interactions for healthcare reporting. Develop APIs, data models, ETL pipelines, and interfaces; optimize performance, ensure data integrity and security, and support automated testing and CI/CD. Collaborate in Agile teams and reduce technical debt while enabling integrations with frontend and third-party systems.

Design, build, and maintain scalable data infrastructure and pipelines for large, varied basketball and performance datasets. Lead technology decisions, implement medallion architectures and data validation, optimize storage and ingestion, and collaborate with cross-functional stakeholders to deliver analytics and application-ready data.

Design, build, and maintain scalable, secure data pipelines and platforms to acquire, transform, and store large financial datasets. Enable AI/GenAI-ready data foundations for model training, inference, retrieval, and RAG workflows. Collaborate with cross-functional teams, ensure data quality, governance, observability, and compliance, and support production deployments and troubleshooting.

Lead the end-to-end Document Crunch data platform: migrate Redshift to Snowflake, build ingestion and transformation pipelines, define data models, enforce data quality and observability, integrate CRM/MDM and Customer 360, enable analytics and AI-enabled data products, and act as the primary technical liaison to the Trimble Data Team to codify enterprise-aligned, code-driven M&A data integration.

Design, develop, and optimize large-scale distributed data systems for real-time and batch processing. Support feature engineering and feature store evolution, build identity graph capabilities, improve observability and performance, and mentor engineers while collaborating with Product, ML, and Data Science teams.

Build and manage automated ETL integrations from customer EMRs, billing, and warehouses into Caris systems. Lead data discovery, validation, and architectural design for clinical informatics and BI. Gather technical requirements, implement access via FHIR/HL7/APIs or direct DB, assemble large clinical datasets, and deliver dashboard-ready data for business users.

Design and lead data lake architecture and Databricks platform solutions for DoW projects. Develop and optimize ETL/Delta Lake pipelines, integrate AI/ML workflows, implement DevSecOps/CI-CD, ensure cloud security and compliance across AWS/Azure/GCP, and liaise between clients and developers to deliver solutions.

Design, execute, and support end-to-end data migrations into SAP S/4HANA: extraction, transformation, validation, reconciliation, and cutover. Partner with functional teams, business owners, and infrastructure to ensure accurate, compliant migrations and provide troubleshooting and documentation.

Design, build, and maintain scalable, secure cloud data pipelines and integrations. Develop APIs and modular components, apply generative AI to pipelines, enforce data governance and compliance for PHI/PII/PCI, mentor engineers, collaborate with analysts and data scientists, and ensure production reliability using containerized deployments and DevSecOps/Agile practices.

Build and maintain production-grade dbt data models and end-to-end data pipelines. Collaborate with Finance, Engineering, Sales, and Product to deliver reliable reporting, analytics, and scalable solutions, reducing manual workflows and ensuring data accuracy.

Design, build, and operate a Snowflake-centered cloud data platform: ingest with Fivetran, transform with dbt, orchestrate with Airflow/Astronomer, ensure observability and data quality, deliver CI/CD workflows, troubleshoot pipelines, guide Cortex Code adoption, and mentor junior engineers while partnering with cross-functional teams.

Lead design and implementation of scalable batch and streaming data pipelines and platforms. Define data architecture standards, drive engineering best practices, mentor peers, and collaborate with product, analytics, and data science to deliver reliable, high-performance data solutions.

Design and develop scalable data architectures and production data pipelines for Finance using cloud and lakehouse technologies. Build ingestion, transformation, data models, and data quality controls with Databricks, dbt, SQL, and Python. Mentor engineers, support migration of legacy ETL, enable audit/SOX-ready processes, and partner with architects and Finance stakeholders to deliver trusted analytics and reporting.

Operate and automate the companys data infrastructure as an SRE: build IaC and self-service tooling for provisioning, scaling, failover, and recovery; optimize relational and non-relational datastores; define SLOs and observability; integrate pipelines and messaging systems; participate in on-call and incident response; reduce operational toil.

Deliver ServiceNow reporting and analytics: define KPI standards, build dashboards/scorecards, maintain reporting datasets and integrations, automate data quality checks, provide operational insights, support release and operations reporting, and partner with global platform and product stakeholders for data-driven decisions.

The Senior Data Engineer will design, build, and optimize data pipelines and models, lead a team, and work with stakeholders to deliver data-driven solutions for a Federal client.

Design, build, and operate scalable, production-grade ingestion pipelines (Fivetran, APIs, files) to bring Workday and other HR/payroll data into the data platform. Ensure data reliability, monitoring, schema management, and handoffs to downstream transformation teams while optimizing connectors, syncs, and costs.

The Cyber Data Science Engineer analyzes large cybersecurity data sets, provides analytics, develops data-driven solutions, and supports compliance reporting while collaborating with team members.