Top Data Engineer Jobs in Portugal

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.

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.

As a Forward Deployed Data Engineer, you will build data management platforms for maritime awareness, implementing data pipelines, models, and improving workflow efficiency. You'll work on-site, writing code and providing technical solutions, ensuring high-performance results.

Develop and maintain Python-based data applications and pipelines: fetch data from databases/APIs/files, build Pandas DataFrames/NumPy arrays, write complex SQL and data transformations, handle nested JSON, and collaborate with data science teams to deliver production data platforms.

Design, build, and maintain scalable data ingestion and ETL pipelines across a growing data lake. Define and enforce data quality standards, SLOs, and validation frameworks. Optimize pipelines for performance and cost, expand monitoring and alerting, and enable stakeholders to self-serve on data infrastructure.

Build and maintain scalable data pipelines, trusted datasets, and reporting systems to support infrastructure deployment, hardware operations, capacity planning, and supply chain analytics. Partner with stakeholders, improve data quality, lineage, and observability, and enable executive reporting, forecasting, and operational reviews. Integrate new telemetry sources and document systems for long-term maintainability.

As a Data Engineer, you will design financial knowledge graphs, create graph processing pipelines, and implement best practices for knowledge graph development.

Build and own customer data ingestion and large-scale pipelines powering AI workers. Design syncing, retrieval, and data lake systems, improve reliability/observability, partner with product/backend teams, and contribute across infrastructure to give AI agents access to enriched customer data.

As an Analytics Engineer, you'll manage the data stack, design database architecture, build data pipelines, and oversee reporting and data quality.

Lead and mentor a data engineering team, define technical vision and strategy, oversee data pipeline design, and collaborate with cross-functional teams.

The Data Engineer will execute data architecture projects, manage data ingestion processes, ensure data quality, and transition data to new systems while collaborating with investment teams.

The Data Engineer will design, implement, and maintain data pipelines, collaborate with cross-functional teams, ensure data integrity and optimize solutions to support analytics and reporting.

As a Senior Data Engineer, you will design and maintain data infrastructure, implement ETL processes, and optimize data workflows using Python and PySpark.

Design and build scalable data lakes, warehouses, and lakehouse architectures. Implement Python ETL/ELT pipelines, orchestrate workflows with Airflow, ingest third-party APIs, optimize columnar formats and query performance, and consult with stakeholders to translate business goals into data architecture roadmaps using Spark, Snowflake, and cloud infrastructure.

Design, build, and maintain scalable AWS-based data pipelines, data lakes and warehouses. Implement data modeling and warehousing for Redshift/Athena, ensure data quality, optimize queries, and develop production-grade Amazon QuickSight dashboards with security (RLS), performance tuning, and stakeholder-driven reporting.

Design, build, and operate high-performance inference platforms for serving large ML models. Focus on request routing, batching, caching, autoscaling, GPU utilization, observability, performance engineering, and production reliability for diverse model workloads.

Design, build, and operate large-scale Hadoop-based data pipelines and analytics platforms. Ingest, transform, and analyze structured and unstructured data to support enterprise analytics, ML, and reporting. Ensure reliable, performant production data platforms and troubleshoot, document, and optimize workflows.

Design, develop, and support cloud-based analytics (Power BI, Snowflake). Build ELT/ETL pipelines, enterprise data models, and Power BI reports. Migrate legacy BI, validate data integrity, enforce security/governance, troubleshoot issues, train users, and support analytics initiatives across the business.

Serve as first point of contact for customers using Agentforce and Data 360, troubleshoot technical issues, provide feature guidance and best practices, manage customer expectations, create and maintain knowledge content, participate in training, and escalate complex issues to internal teams to ensure customer success.

Lead design and delivery of production data platforms, pipelines, and analytics. Architect Snowflake/Databricks solutions, build ETL/streaming ingestion, implement dbt transformations, data quality, observability, and governance, support BI and AI/ML feature/data pipelines, and mentor engineers while driving DataOps and platform best practices.

Design, build, and operate production LLM-driven agents that discover and verify business web presence, link people to entities, score legitimacy/risk, and maintain shared agent infrastructure (tool registry, eval harness, instrumentation). Own model selection, prompt/tool engineering, eval methodology, and cost/latency optimization for enrichment pipelines.

Design, build, and operate reliable, scalable backend services and platform capabilities for monetization (pricing, billing, ads, payments). Own architecture, integrations, correctness, observability, and operational excellence. Lead cross-functional technical projects, write RFCs, mentor engineers, and deliver reusable developer tools and data products for product, finance, and GTM teams.

Build, test, and deploy scalable data platform services supporting ETL/ELT, streaming, and analytics. Collaborate with global teams, troubleshoot production issues (on-call), optimize performance, and maintain documentation and observability for platform reliability.

Design, build, test, and deploy scalable data platform services (ETL/ELT, streaming, batch) using cloud and distributed processing frameworks. Support production on-call, collaborate with global teams, improve performance, and maintain platform documentation and observability.