Top Data Engineer Jobs in Portugal

Provide production support for SQL Server databases, ETL/data integration, Azure cloud services, and enterprise reporting. Monitor performance, troubleshoot issues across Windows and Linux servers, support file transfers and enterprise applications, and collaborate with technical teams to ensure data availability and reliability.

Own and evolve Redfin's analytics data warehouse and data lake. Design dimensional data models, build and tune ETL pipelines, write performant SQL, implement data ingestion and storage solutions, deliver end-to-end features, and collaborate with Analytics and Engineering to support production data needs.

Design, build, and deliver Power BI dashboards and analytics solutions using AWS, SQL, and Python. Develop data models, ETL pipelines, and analytics logic; incorporate AI/ML where appropriate. Partner with stakeholders, IT, and vendors to gather requirements, test solutions, and translate insights into business decisions to improve customer experience for a utility program.

Design, implement, and maintain large-scale data pipelines and storage. Build ETL processes, integrate data sources, optimize big-data workflows using Hadoop/Spark/Kafka, manage data lakes/warehouses, implement and operate Elasticsearch clusters, and collaborate with data scientists to support analytics and continuous improvement.

Design, build, and maintain scalable, high-performance data pipelines, ingestion, transformation, and data export solutions. Implement data quality, testing, and monitoring, collaborate with product and stakeholders to build analytical data models, support production jobs, perform PoCs, and contribute to roadmap, standards, and documentation.

Develop, maintain, and troubleshoot ETL solutions and system interfaces to move and transform data across health system applications and a data warehouse. Design integration architecture, code and test interfaces, document solutions, and propose improvements. Support existing data transfers and stay current with ETL and API technologies.

Design, build, and maintain data collection, storage, and full‑stack applications for manufacturing and test data. Implement CI/CD, APIs, databases, and deployment architecture; support internal users and test teams; mentor junior developers and follow software best practices.

As a Software Engineer, you will build core data systems, collaborate on new features, and improve team productivity within a hybrid working environment.

The Senior Data Engineer designs, develops, and maintains ETL pipelines and database systems while ensuring data security and compliance with HIPAA. Responsibilities include SQL development, data integration, reporting, and collaborating with teams to support data needs.

Design and implement SAP S/4HANA integrations: map legacy data to S/4 structures, build/validate OData/REST APIs and integrations via SAP BTP/Integration Suite and Datasphere, support Okta provisioning/SCIM, troubleshoot end-to-end workflows, produce documentation, and support testing, cutover, and post-go-live stabilization for public-sector modernization.

Design, build, and optimize scalable batch and streaming data pipelines. Model and process structured and unstructured data, ensure production reliability and observability, apply ML techniques for insight extraction, and drive data strategy while adopting modern tooling and IaC practices.

Design, build, and maintain data pipelines and analytics-ready datasets using SQL and cloud data platforms. Perform data profiling, validation, and source-to-target mapping. Support BI enablement, document transformations, and collaborate with stakeholders while following data governance and security practices.

Design, build, test, and maintain ETL/ELT data integration pipelines and data architecture. Perform data mapping, profiling, quality remediation, and support BI/analytics by partnering with business and technical teams. Provide full lifecycle support, documentation, and continuous improvement in a hybrid agile environment.

Lead delivery of enterprise data governance, MDM, and modern data-platform components including Snowflake, CDC pipelines, schema-first contracts (JSON Schema/Avro/Protobuf), data catalog and PII classification, CI/CD schema management, AWS data services, and day-to-day leadership of an offshore delivery team.

Lead design, configuration, and delivery of advanced automation and control projects for microgrids, data centers, and critical infrastructure. Provide control system architecture, manage project scope/schedules/budgets, oversee testing/commissioning, collaborate with global teams, and drive process improvements and innovation.

Build and optimize Ray Data: improve performance and scaling for multi-modal batch inference, implement production data-loading solutions, ensure stability and fault tolerance at high scale, and collaborate with customers to scale AI workloads.

The Sr. Data Engineer will design, implement, and optimize data solutions in Snowflake, collaborate with clients, and mentor junior engineers.

Design, build, and maintain scalable data pipelines and a customer-facing recommendation engine (including LLM logic). Manage data warehouse, data quality monitoring, CI/CD for pipelines, and partner with product, analytics, engineering, and marketing to ensure consistent metrics and observability.

Build and own data platform infrastructure and scalable pipelines (ingestion, orchestration, transformation, delivery). Define governance, observability, and AI-first architecture. Optimize performance, ensure data quality, mentor engineers, and integrate AI-assisted tooling.

Lead design, build, optimization, and operation of scalable Databricks-based batch and streaming data pipelines for healthcare programs. Ensure DataOps, data quality, lineage, observability, CI/CD, and compliance with CMS and federal healthcare regulations. Collaborate with architects, data scientists, and stakeholders, troubleshoot production issues, and mentor junior engineers.

Senior Staff Data Engineer designs, builds, and owns cloud-based ETL/ELT pipelines and data products for Sales and Underwriting. Responsibilities include solution architecture input, CI/CD implementation, data quality and replication, hybrid cloud integration (AWS/Azure), mentoring, and evaluating new data technologies to support analytics and operational decision-making.

Design, build, and optimize scalable end-to-end data pipelines and Snowflake data warehouses. Develop BI solutions (Power BI/Tableau/Cognos), enforce data quality/governance, integrate investment data vendors, collaborate with stakeholders, mentor junior engineers, and follow SDLC/DevOps best practices.

Design, build, and operate large-scale data acquisition pipelines and backend services. Implement ETL/ELT for batch and streaming flows, develop Java production services, ensure schema evolution and data quality, optimize performance and cost, and provide observability. Collaborate with product, data science, and platform teams to translate requirements into production-ready systems.

Build and operate data-intensive web products and APIs, extend high-throughput ETL pipelines and scrapers, ensure reliability/observability, design self-scaling services, participate in code review, and collaborate across product, data, and infrastructure teams to meet production SLAs.

The Data Engineer designs and maintains scalable data products, implements quality checks, and supports analytics and reporting needs, collaborating closely with business stakeholders to ensure data reliability.