Top Data Engineer Jobs in Portugal

Design, ingest, validate, and manage complex financial and annuity data from external partners. Build and maintain ETL pipelines, SQL queries, and data quality controls; investigate data anomalies; collaborate with Accounting, Actuarial, and Technology; support reporting and process automation to improve financial and regulatory workflows.

Lead design, development, and optimization of ETL/ELT pipelines and data products for telematics and third-party data. Ingest large-scale datasets into the enterprise data lake/lakehouse, implement CI/CD and DataOps practices, orchestration (MWAA/Autosys/Control-M), observability, and resilient self-healing pipelines. Mentor team members, collaborate with architects, data scientists, and BI teams, run POCs, and apply RAG and AI-driven systems while ensuring governance, security, performance, and data quality.

Design, build, and maintain scalable semantic 360 data models and transformation pipelines. Implement cleansing, enrichment, business rules, KPIs, and scoring algorithms using SQL and Python/Scala. Employ AI coding assistants and modern AI engineering practices to accelerate development while ensuring traceability, data quality, performance, and alignment with product and analytics needs.

Lead Data Engineer/ETL role requiring 5-10 years of Informatica ETL experience. Responsibilities focus on BDM, TDM, data quality, big data, data warehousing, and star schema design. Strong verbal and written communication and a technical bachelor’s degree required. Unix experience is a plus.

Design, build, and optimize SQL Server-based data layers and Azure data solutions. Own query performance, indexing, concurrency, CDC pipelines, ORM data access patterns (C#), and database CI/CD. Partner with engineers and architects, mentor team members, and ensure scalable, low-latency data platforms.

Design, build, and operate secure, scalable cloud-native backend systems for unstructured data and AI workloads. Partner with platform, security, and ML teams to create microservices, APIs, and data pipelines, deploy large-scale ML models, and deliver self-service capabilities while prioritizing privacy, ethics, and reliability.

Hands-on data and integration engineer responsible for building, supporting, and automating Canoe-related workflows and integrations. Develop and maintain data pipelines, SQL queries, validations, reconciliations, and monitoring to deliver alternative investment data to Snowflake, Addepar, reporting tools, and downstream systems. Troubleshoot data quality issues, support production feeds, manage exceptions, document mappings and runbooks, and collaborate with investment, reporting, technology, and vendor teams. Hybrid role requiring Baltimore office presence three days per week.

Lead a team building and operating large-scale, reliable data pipelines and warehouses. Mentor engineers, partner cross-functionally, manage SLAs, embed AI/LLM-driven Data Ops, and drive end-to-end delivery of canonical datasets and data infrastructure.

Remote entry-level data science engineer role building end-to-end data science applications: data preparation, exploration, feature engineering, modeling, automation, and distributed model implementations using Python, SQL and scalable paradigms (MapReduce/PySpark). Must show real-world full-cycle project experience and readiness to learn PySpark quickly.

Remote entry-level Big Data Engineer role building data acquisition and munging pipelines. Requires strong Python3 (NumPy, Pandas), advanced SQL, scalable algorithm and data-structure implementation on distributed clusters, converting code to functional paradigms, and the ability to learn PySpark or Kafka quickly. Product-development, startup experience and real-world pipeline projects preferred.

Serve as the on-site operations representative for data center construction, enforcing QA/QC standards, conducting inspections and walkdowns, coordinating with design and commissioning teams, reviewing MEP designs for maintainability, documenting progress and test results, and resolving engineering issues to ensure construction meets operational requirements.

Build and document DBT models in Snowflake, develop and maintain Tableau dashboards, handle data operations and troubleshooting, modernize data infrastructure, and own stakeholder relationships and requirements.

Design and build scalable GenAI and ML systems: ingest, transform, store, serve, and govern data for LLM-based features. Implement RAG, embedding and retrieval layers, knowledge graphs, model integration, monitoring, evaluation, and production deployments while building batch and streaming feature pipelines.

Provide operational and data support for wind tunnel test engineers: configure and maintain data acquisition systems (DAS), process and validate test data, ensure DAS availability and backups, deliver validated data, support instrumentation setup, and recommend software enhancements to improve reliability and performance.

Lead presales for Data Analytics/AI solutions, secure technical closes, scope and design solutions with sales and delivery, hit productivity quotas, coach sales associates, manage partner relationships, and drive product growth and customer satisfaction.

Designs and implements scalable real-time and batch data pipelines, optimizes performance and reliability, applies ML libraries and quantitative methods, builds cloud-native AWS data platform components, develops CI/CD and orchestration, performs testing/validation and documentation, and collaborates on data-centric initiatives in a financial services environment.

Build, maintain, and optimize cloud data pipelines and dbt models; design Airflow DAGs; implement dimensional models and BI dashboards; integrate healthcare data with HIPAA-compliant practices; contribute to RAG pipelines and MLOps workflows; review contractor code, monitor data quality, and document designs following governance standards.

Design, build, migrate, and maintain scalable data pipelines and architectures on Azure and Microsoft Fabric. Implement ETL/data integration, semantic models for analytics, CI/CD, monitoring, security controls, cost optimization, and testing. Collaborate with cross-functional teams and clients to translate business requirements into reliable, compliant data solutions.

Build and operate the data platform powering Vantaca IQ: ingestion and CDC pipelines, data modeling, aggregations and materializations, multi-tenant isolation, query/metrics APIs and reporting surfaces, LLM grounding/eval harnesses, and governed semantic layers to serve humans and agents with trustworthy intelligence.

The Senior Data Engineer will design and maintain data pipelines, ensuring data reliability and consistent models, while collaborating with stakeholders to improve data practices.

Develop scientific software for AI-native drug discovery, building data pipelines, APIs, and lab automation integrations while collaborating with scientists.

The Principal Solutions Engineer will lead efforts in data center power infrastructure, promoting superconducting solutions, and collaborating with engineers and executives to drive technology adoption.

The role involves architecting and scaling data processing pipelines, building a data platform for ad serving, and transforming complex business strategies into efficient systems. Strong backend expertise in large-scale data systems is required.

The Senior Data Infrastructure Engineer designs and scales data platforms on AWS, optimizing performance, cost, and security while mentoring junior engineers.

The Lead Software Engineer will design, develop, and support scalable cloud-based messaging and integration platforms, provide technical leadership, and ensure performance and reliability across platforms, primarily using Java, Spring Boot, and AWS services.