Top Data Engineer Jobs in Portugal

The Data Engineer will design databases, develop ETL tools, optimize SQL, and work with cloud platforms while ensuring data performance for clients.

Design and build scalable cloud-native data pipelines and models to produce trusted, analysis-ready data. Ensure data quality, governance, and privacy controls, apply software engineering best practices, enable BI and AI/ML consumption, and collaborate with clients and cross-functional teams.

Design, develop, and manage scalable database systems, data pipelines, structures, and load routines primarily in AWS RDS for PostgreSQL and SQL environments. Support application teams through APIs, database optimization, data processing, and reporting tools such as Power BI. Collaborate with technical and non-technical stakeholders in an Agile setting. The role requires U.S. citizenship and an active TS/SCI with Polygraph clearance.

Develop and deploy high-performance, highly available Java server-side applications and evolve existing systems into large-scale service architectures. Apply object-oriented design, architectural patterns, distributed computing frameworks, serialization technologies, REST, SQL, unit testing, mocking, and build tools. Work with Hadoop ecosystem technologies and learn emerging big data analytics platforms.

Design, develop, and optimize scalable batch and real-time data pipelines on GCP. Implement Medallion Architecture, build Python and PySpark transformations, optimize BigQuery and SQL workloads, deploy Dataflow pipelines, and orchestrate workflows with Cloud Composer and Airflow. Manage GCS storage, CI/CD, version control, IAM, data governance, security, reliability, scalability, and cost efficiency across enterprise data platforms.

Develop and maintain cloud-based data platforms supporting data science applications and services. Responsibilities include cloud infrastructure administration, system operations, monitoring, troubleshooting, security accreditation support, account and credential management, repository maintenance, and backup and restoration. The role also involves deploying environments, automating infrastructure and application delivery, supporting containers and orchestration, and collaborating with software development teams in controlled security environments.

Provides technical support for data services by troubleshooting access, quality, and availability issues; resolving customer tickets; documenting solutions; training users; monitoring service health; tracking support metrics; coordinating with technical teams; and supporting change management, escalation procedures, proactive monitoring, and new platform features.

Provides technical leadership for enterprise data platform engineering. Designs and implements ETL, ELT, streaming ingestion, data models, cloud data lakes and warehouses, monitoring, data quality, governance, testing, version control, and CI/CD practices. Leads AWS, Snowflake, and dbt implementations while integrating disparate data sources for analysts and data scientists. Partners with business stakeholders to align data products with organizational strategy and enables self-service analytics and automation.

The Staff Data Engineer will lead the architecture and scalability of H1's healthcare data processing systems, ensuring efficient entity resolution and big data operations. Responsibilities include design and optimization of distributed Spark pipelines, team leadership, and collaboration with AI/ML teams to enhance data processing capabilities.

Implements and supports security data ingestion pipelines across applications, cloud services, infrastructure, security tools, and business systems. Develops transformations, parsing, normalization, enrichment, masking, validation, and delivery workflows. Troubleshoots data quality and pipeline issues, documents architectures and data flows, coordinates with client stakeholders, and supports SIEM, detection, investigation, observability, and automation use cases. Requires data engineering experience, scripting, query languages, integration knowledge, and strong client communication.

Design, build, and operate the GraphQL API platform that routes high-volume traffic. Deliver end-to-end projects, improve reliability and performance, own SLOs and incident response, mentor engineers, and collaborate with product teams to evolve platform APIs and tooling.

The Senior Research Engineer will curate large datasets, automate data pipelines, optimize queries, and support data-driven research impacting business outcomes.

The Senior Data Engineer will manage data pipelines, design data infrastructure, implement ETL processes, and ensure high data quality across teams.

Build and operate Numeric’s financial data platform, including scalable ingestion pipelines, typed data contracts, lakehouse schema management, data security, event-driven processing, observability, and reporting infrastructure. Work across TypeScript services, SQL, ClickHouse, Postgres, and transformation tools while partnering closely with accounting, reporting, and AI teams.

Build and operate Numeric’s financial data infrastructure, including ingestion pipelines, typed data contracts, lakehouse schemas, batch and event-driven processing, security controls, observability, and scalable reporting. Work across TypeScript, SQL, and Python while collaborating with accounting, reporting, and AI teams to deliver reliable, auditable, multi-tenant financial data systems.

Build and own the architecture for Dune’s curated data lifecycle, including dependency-aware orchestration, backfills, schema evolution, retries, recovery, data quality, and alerting. The role combines backend software engineering with large-scale data systems work across Go, Kotlin, Rust, Python, and SQL. Responsibilities include designing ingestion and curation contracts, making architecture decisions, solving ambiguous problems, and leading work that other engineers can execute.

Build and extend automated enterprise data governance and quality frameworks. Define measurable trust rules, data contracts, validation and certification workflows, metadata, lineage, tagging, and trust scoring across a cloud data platform. Integrate governance checks into developer workflows and Collibra, coach engineering and product teams, and establish organization-wide data trust standards. The role requires strong SQL, BigQuery or comparable warehouse experience, and expertise with data quality or observability tools.

Design and implement scalable data integrations and transformation layers for cybersecurity products. Build data contracts, dimensional/incremental models, observability, and lineage tooling. Collaborate with product engineering to integrate SIEMs (Sentinel, Splunk) and deploy cloud/on-prem solutions on Kubernetes/Docker, processing medium-to-large datasets and stream/message systems.

Lead the design, development, scaling, and operation of enterprise data platforms, services, and pipelines. Own mission-critical systems, deliver complex multi-team projects, build analytics solutions, and improve data delivery processes. Partner with architects, engineers, analysts, data scientists, and business stakeholders to create reliable, observable, secure, and governed platforms. Provide technical leadership, evaluate technologies, establish engineering best practices, mentor engineers, and guide technical decisions across teams.

Design, develop, and optimize cloud-based ETL/ELT pipelines and data architectures using Informatica and Databricks in AWS GovCloud. Author and optimize SQL and Python scripts, build secure RESTful APIs, perform data validation, migrations from on-premises to cloud, and troubleshoot performance issues across large datasets. Support DON Jupiter enterprise environment and related ETL frameworks.

Develop scalable planning analytics and automation for a global supply chain: build data pipelines and models (demand forecasting, inventory optimization, capacity/backlog modeling), support SIOP scenario planning, operationalize analytics with IT, establish data governance and standards, and train/mentor analysts to embed analytics into decision-making.

Design, build, and optimize large-scale ETL pipelines and data models powering player and publishing insights. Architect high-performance data solutions, automate workflows, ensure data quality and compliance, mentor engineers, optimize costs and query performance, and drive tooling/standards for centralized analytics at scale.

Build, deploy, and maintain secure, scalable data pipelines and analytics on AWS/Databricks. Implement CI/CD, governance (Unity Catalog, lineage), platform observability, and operational support for enterprise datasets and Databricks SQL reporting.

Lead design and delivery of scalable data pipelines and APIs for Digital Risk Protection. Mentor engineers, align and ingest multiple data streams (including graph data), productize analytics and LLM outputs, and drive DRP technical projects with stakeholders to enable data-driven intelligence.

Designs and oversees scalable data platforms, warehouses, lakehouses, pipelines, ETL processes, dimensional models, and Spark workloads. Integrates AI/ML capabilities, data governance, lineage, testing, monitoring, and performance optimization. Collaborates with engineering, product, DevOps, and security teams to support tracking, analytics, and business insights. The role also mentors engineers and analysts and manages software delivery using AWS DevOps, CI/CD, and Terraform practices.