Top Data Engineer Jobs in Portugal

Intern will explore and clean unfamiliar datasets, write code to ingest, transform, and monitor data quality using Python, SQL, and OCaml, work with structured and unstructured data, complete two owned projects, and be mentored by full-time Data Engineers.

Build and scale core data infrastructure and foundational datasets. Design, develop, and maintain scalable data pipelines for analytics, ML, experimentation, and product use cases. Implement data quality, audits, alerting, and anomaly detection. Partner with product, engineering, and business stakeholders and help establish long-term, scalable data architecture and tooling.

Build and scale ML development infrastructure and Agentic AI tooling. Optimize distributed training (PyTorch/DDP), improve GPU utilization, design multi-cloud Kubernetes environments, and collaborate with ML researchers and engineers to streamline the ML lifecycle.

Lead the technical strategy and architecture for a scalable clinical data platform. Drive cross-team engineering initiatives, redesign legacy data pipelines, build batch and streaming systems, develop deployment and self-service tooling, improve monitoring, manage data models and governance, ensure privacy and security, and mentor engineers. Partner with product, AI, infrastructure, health systems integration, and business intelligence teams to deliver reliable, extensible data capabilities.

Designs, builds, and optimizes scalable AWS and Snowflake data pipelines, infrastructure, data models, semantic layers, and data quality frameworks. Analyzes Medicare, Medicaid, and CMS repository data to support analytics and reporting. Responsibilities include workflow monitoring, automation, governance, security, performance optimization, stakeholder collaboration, and Agile delivery using modern DevOps and software engineering practices.

Own end-to-end data engineering for a business domain, including API and other-source ingestion, dbt models, orchestration, data-quality testing, monitoring, documentation, and performance. Build reliable, AI-ready single sources of truth and ensure data freshness, accuracy, traceability, and scalability. Collaborate with stakeholders and the Director of Data, establish engineering patterns, review work, and mentor other engineers.

Leads the design, development, testing, deployment, maintenance, and production support of Appian applications for a federal health research client. Translates requirements into workflows, interfaces, integrations, and case management solutions; supports full SDLC activities, release management, accessibility, quality assurance, incident resolution, documentation, and Agile delivery. Collaborates with federal stakeholders and technical teams while contributing to modernization, compliance, knowledge transfer, and process improvement.

The Data Engineer will build and optimize data pipelines and infrastructure, ensuring data quality for analytics and machine learning initiatives while collaborating with teams to develop data solutions.

Support the Data team by building and maintaining scalable ETL pipelines and data infrastructure for multi-modal medical datasets, automate data QA, optimize data delivery on cloud platforms, and provide analytics tools and secure cross-border data storage.

Design and implement end-to-end data integration and warehousing solutions for large volumes. Implement Hadoop/Hive data movement, script in Linux shell and Python, develop SQL for integration and analysis, and perform high-volume DW performance tuning. Vertica experience is a plus. Requires technical independence and a BS in CS/EE.

Design, architect and manage AWS Big Data solutions; build and tune Hadoop-based ETL/ELT pipelines; process unstructured and real-time data; develop with Java/Python/C++/scripting languages; collaborate on BI/visualization; ensure performance and robust workflows. 6-month contract, US work authorization required.

Lead design, development, and deployment of data reporting and dashboard solutions for Client Service Training. Work with project leadership to create tables/files, run ad-hoc reports, validate results, automate scheduled reports or integrate with dashboard tools, and communicate insights using BI and statistical tools.

Onsite voice/data engineer to troubleshoot, install, configure, and document network and VoIP systems. Work includes routing/switching (OSPF/BGP), Cisco platform integration, SNMP monitoring, cabling (Cat5e/Cat6/fiber), responding to trouble tickets, and occasional after-hours or emergency support.

Build and implement a transactional data system: design and develop SSIS ETL packages, consume web services in ETL, create SSRS reports for ETL status, and implement T-SQL/SQL Server solutions per functional requirements and system design.

Design, build and maintain a data transactional system performing ETL and web service calls to synchronize state between systems. Develop SSIS packages, data models, dictionaries, test plans, and assist architects on database strategy.

Develop ETL, reporting, and OLAP solutions using SQL Server (SSIS, SSRS, SSAS) and T-SQL; perform impact analysis, document requirements, support ETL/data quality, and assist database architecture and defect resolution.

Implement OLTP and OLAP systems to persist court information from functional requirements and system design. Perform ETL, export data to external agencies, use managed service calls, design and model database structures, design/code/deploy SSIS packages, document data dictionaries and package definitions, develop SSIS test plans, and support architects.

Design, develop, and optimize Teradata data solutions: elicit requirements, create logical/physical designs, write SQL (views/procs/macros), use Teradata utilities for data loads, tune performance for large datasets, coordinate stakeholders, and write Unix shell scripts.

Elicit and analyze requirements; design logical/physical Teradata solutions; develop ETL using Teradata utilities; write SQL (views, stored procedures, macros, functions); perform performance tuning for large datasets; write Unix shell scripts; coordinate with stakeholders and support BI/DW initiatives.

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.

The AWS Engineer will develop and support cloud-based solutions, migrate on-premise assets to AWS, optimize workloads, and guide the engineering team.

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

Build and maintain Azure Data Factory ingestion pipelines into Snowflake, implement medallion transformations (Coalesce), write Python orchestration and connectors, apply governance with Atlan, collaborate with AI coding agents, participate in CI/CD with Azure DevOps, handle on-call production support, and document runbooks.

The Senior Data Engineer will design and implement lakehouse architectures, optimize ClickHouse deployments, develop ETL/ELT pipelines, and create data models to support analytical and operational functions.

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