Data Engineer

• Support the maintenance and continuous improvement of the data platform
• Ensure data remains accurate, reliable and consistently up to date
• Monitor daily ELT processes and ensure pipelines run successfully within expected timeframes
• Identify and investigate data quality issues, pipeline failures and inconsistencies
• Transform raw data from different sources into structured and usable datasets
• Work with healthcare data, including HL7, laboratory results, appointments and admissions
• Support development and maintenance of data models and transformations
• Collaborate with Data Analysts and other teams to understand data needs and provide reliable solutions
• Communicate technical topics clearly to non-technical stakeholders
• Contribute to documentation, testing and continuous improvement of data processes

Junior Data Engineer

• Support a broad set of architectural needs across multiple workstreams
• Design and own the data layer behind GenAI, RAG, and Agentic AI applications
• Ensure enterprise data and knowledge are ingested, prepared, stored, governed, and made available for AI consumption and retrieval
• Own and design data architecture, data modeling, ingestion, and platform modernization for enterprise Azure environments
• Design and implement scalable, metadata/configuration-driven data ingestion and data platform solutions
• Work with structured and genuinely unstructured data across the enterprise platform
• Modernize existing data platforms and ensure implementation-ready architecture

Senior Azure Data Architect – GenAI, RAG, Agentic AI

• Build ingestion and transformation pipelines that populate the Knowledge Graph from internal systems, enrichment outputs and third-party sources.
• Implement entity resolution and linking logic in production.
• Manage late-arriving data, conflicting sources and graph schema changes over time.
• Build query and serving layers used by search, matching and data product teams.
• Model the graph for analytical and application use cases across BigQuery, PostgreSQL and Elasticsearch / OpenSearch.
• Support external-facing data products with reliable export and delivery pipelines.
• Implement data quality checks, lineage and monitoring across graph pipelines.
• Own production operations, including alerting, backfills and incremental reprocessing.
• Contribute to data contracts so downstream teams can rely on the graph.

• Work as part of software delivery teams
• Help clients build production-grade data foundations
• Contribute to modernisation, platform, data, and AI-readiness engagements
• Use Databricks as the primary data engineering platform
• Build durable, well-crafted data systems with production focus

Senior Data Engineer – AI

• Build reliable data pipelines and platform capabilities powering customer-facing data movement, analytics data products, and machine learning foundations
• Lead large-scope or high-impact projects and drive technical decisions through ambiguity
• Own architecture and end-to-end delivery of critical data ingestion and activation workflows, including source connectors, staging and transformation, diffing, incremental sync, and Iterable bulk API integrations
• Define high-availability, fault-tolerance, and recovery patterns including graceful degradation, retries, replayability, backfills, idempotency, and durable workflow execution
• Lead Snowflake-based data pipelines and data-sharing workflows
• Establish technical standards for schema evolution, data quality, observability, testing, and lifecycle management
• Partner with data science and machine learning engineers on feature generation, feature serving, model inputs, and experimentation workflows
• Drive tradeoffs across batch and streaming, data modeling, latency, performance, cost, availability, and maintainability
• Collaborate with product, frontend, platform, SRE, and customer-facing teams to define interfaces and resolve production issues
• Identify architectural gaps and operational risks and create roadmaps, design proposals, and execution plans
• Create reusable abstractions, platform capabilities, and engineering patterns
• Provide technical leadership through design reviews, implementation guidance, incident reviews, and mentorship
• Influence roadmap and prioritization discussions
• Participate in operational support or on-call as needed

Staff Data Engineer

• Work on strategic data initiatives
• Build and operate reliable, scalable data products on clients’ Palantir-based data platform
• Design, build, and maintain scalable data pipelines and data products using Palantir
• Develop data transformations using Python and PySpark
• Build robust ETL/ELT workflows integrating multiple data sources
• Write efficient SQL for data transformation and analytics
• Design and maintain data models optimized for analytical use cases
• Collaborate with business and analytics stakeholders to translate requirements into data solutions
• Ensure data quality and reliability through testing, monitoring, and CI/CD
• Analyze data to identify inconsistencies and improvement opportunities
• Document solutions and contribute to data engineering best practices

Data Engineer jobs in Portugal

Junior Data Engineer

Senior Azure Data Architect – GenAI, RAG, Agentic AI

Data Engineer

Senior Data Engineer – AI

Staff Data Engineer

Senior Data Engineer, Palantir focus