Top Data Engineer Jobs in Portugal

Leads 24/7 operations, maintenance, troubleshooting, and emergency response for data center infrastructure. Maintains electrical, mechanical, fire/life safety, controls, security, and building systems, including generators, UPS equipment, switchgear, chillers, CRAC units, BMS, and CMMS. Interprets construction documents, coordinates drawing updates, performs repairs, supports continuous facility resilience, and communicates with internal and external customers. The role requires on-site availability in Charlotte, North Carolina, applicable operating licenses, Universal CFC certification, and authorization to work without sponsorship.

Design and lead scalable data architecture and AI pipelines that transform disparate and unstructured data into production-ready organizational intelligence. Build batch and streaming integrations with Snowflake, optimize databases through sharding, replication, indexing, and normalization, and support relational, vector, graph, and document data models. Collaborate with data scientists and analysts, develop enabling frameworks, document architecture, and guide production-ready AI infrastructure across AWS and enterprise platforms.

Designs and scales enterprise backend services, data platforms, pipelines, and distributed processing solutions. Leads architecture, graph-based data initiatives, Snowflake implementations, engineering standards, code reviews, CI/CD, testing, and AI-assisted development. Partners with technical and business stakeholders, ensures security and regulatory compliance, optimizes platform performance, and mentors engineers.

Design, build, deploy, and support production data pipelines and enterprise data solutions in Databricks and GCP. Develop data models and layered architectures, ensure data quality, security, and governance, integrate multiple sources, and support analytics, AI/ML, reporting, and operational decision-making while collaborating with technical teams and federal stakeholders.

Develops advanced data engineering and visual analytics applications for structured and semi-structured data. Designs enterprise database systems, builds large relational databases, develops and optimizes data pipelines, integrates systems with existing data warehouses, and improves system performance. Requires Java, AWS, ETL, Spark, Scala, SQL, PostgreSQL, NiFi, Informatica, and Linux experience, along with an active Top Secret/SCI-eligible clearance.

Architect and maintain secure, scalable data platform infrastructure and resilient batch and streaming pipelines. Build infrastructure using Terraform and Helm, deploy cloud data services, optimize schemas and database performance, and implement monitoring and alerting. Partner with application teams to resolve data issues, establish governance practices, and support MLOps through model versioning, containerization, and deployment.

Build and oversee reliable ETL/ELT pipelines and data products that transform complex customer data into trusted analyses, visualizations, quality reports, and AI-powered insights. Responsibilities include data exploration, quality control, anomaly detection, AI/ML output evaluation, customer collaboration, documentation, and improving data-cleaning and analytics tools. The role requires cross-functional work in an Agile environment focused on security, data integrity, and clear communication.

Build and maintain ETL/ELT pipelines, explore and clean complex customer data, and deliver trusted analytics products, reports, visualizations, and AI-powered data capabilities. Partner with customers and internal teams to define data requirements, investigate discrepancies, validate AI/ML outputs, implement quality controls, and improve data tooling through automation. Translate complex findings and workflows into clear narratives and repeatable processes.

Architect and maintain secure cloud data infrastructure, scalable schemas, and resilient batch and streaming pipelines. Deploy data platforms using Terraform, Helm, CI/CD, and infrastructure-as-code practices. Build monitoring and alerting for data health, system performance, and container observability. Troubleshoot application workflows, database queries, and pipeline logic while advancing data governance. Support MLOps through AI model versioning, containerization, and deployment.

Monitors and maintains critical data center systems, including mechanical, electrical, cooling, generator, fire suppression, and UPS equipment. Performs inspections, preventive maintenance, troubleshooting, installations, work order management, documentation, inventory tracking, and incident response. The role follows safety and regulatory procedures, coordinates with vendors and contractors, supports equipment upgrades, and works scheduled shifts, holidays, and rotating on-call coverage in an on-site environment.

Support data centre operations through installation, migration, maintenance, troubleshooting, break-fix, and decommissioning of compute, networking, storage, and high-density AI infrastructure. Perform smart hands support, cabling, site surveys, documentation, safety procedures, and on-call incident response while collaborating with engineering, project management, customers, and vendors to maintain uptime and service levels.

Designs, develops, and maintains IBM Planning Analytics and TM1 models, cubes, applications, rules, feeders, and TurboIntegrator processes for financial planning, forecasting, reporting, and actuarial modeling. Builds data ingestion, transformation, quality, masking, and curation processes; supports SQL development, security, performance monitoring, and critical data pipelines. Partners with finance and actuarial stakeholders, provides operational support, develops scalable tested code, and mentors team members.

Leads an engineering team building scalable ML data infrastructure, including data ingestion, processing, storage, access, pipelines, and analytical platforms. Defines architecture, evaluates technologies, improves performance and reliability, translates data requirements into technical solutions, and ensures governance, security, and regulatory compliance. Provides mentorship, strategic roadmap input, and cross-functional collaboration with ML engineers, data scientists, platform engineers, and product teams.

Leads the design, administration, optimization, and modernization of enterprise data platforms across SQL Server, Azure, and Microsoft Fabric. Responsibilities include database operations, high availability and disaster recovery, performance tuning, replication, cloud migrations, monitoring, security, governance, and automation. The role collaborates with architects and infrastructure teams, mentors junior engineers, and serves as a subject matter expert for database infrastructure and cloud architecture.

Designs, builds, and maintains scalable ETL/ELT pipelines and finance data models using Snowflake, AWS, dbt Core, Python, and SQL. Develops Medallion architecture data marts, integrates ERP systems, and partners with stakeholders on financial workflows. Implements data governance, RBAC, automated quality testing, observability, documentation, CI/CD, and secure deployments. Monitors Snowflake costs and optimizes queries while supporting Oracle EBS integrations and the migration to Workday.

The Principal Data Engineer will lead data engineering efforts on public cloud, design scalable solutions, build data pipelines, and drive deliverables with a high level of technical expertise in relevant technologies.

Leads the architecture, development, modernization, and operation of enterprise data platforms and pipelines supporting credit risk, analytics, regulatory reporting, and AI initiatives. Builds scalable cloud lakehouse solutions using Databricks, Spark, Delta Lake, Python, and SQL; establishes governance, quality, lineage, observability, and compliance controls; optimizes performance and costs; leads technical initiatives; influences architecture; mentors engineers; and partners with product, analytics, science, engineering, and business stakeholders.

Leads the design and management of scalable cloud database infrastructure across AWS and Azure. Responsibilities include PostgreSQL and SQL Server administration, GraphQL and Hasura API development, cloud migrations, CI/CD automation, infrastructure as code, performance monitoring, security, compliance, data modeling, and mentoring engineers. The role also supports data access layers for AI and application workloads.

Leads architecture and hands-on development of scalable data pipelines, governed data models, semantic layers, analytics products, and AI workflows. Writes production SQL and Python, establishes engineering standards, mentors engineers, and drives design reviews. Builds agentic and LLM solutions using retrieval and managed AI services while ensuring data quality, observability, reliability, privacy, and regulatory compliance for PHI and genomic data. Partners with stakeholders, platform teams, and governance forums to deliver trustworthy business solutions.

Supports scalable ETL/ELT pipelines, cloud data platforms, database integration, machine learning model development and deployment, AI-enabled workflows, and analytics dashboards. Uses Python, data science libraries, AWS, GCP, Azure, SQL and NoSQL databases, Looker, Tableau, and automation tools. Collaborates with data engineers, analysts, data scientists, and marketing teams to deliver data-driven solutions. The role is hybrid in Dallas, requiring two in-office days weekly.

Conducts electronic warfare research, mission data development, validation, verification, and testing. Supports EW system programming and reprogramming, coordinates requirements with system engineers, prepares test plans, manages configuration control boards, and analyzes post-test data. The role requires domestic and international travel, U.S. citizenship, technical education or equivalent experience, systems design expertise, and eligibility for a Secret clearance.

Conducts electronic warfare research, mission data development, validation, verification, and testing. Supports EW system programming and reprogramming, develops test plans, participates in configuration control boards, and performs post-test data analysis. The role requires collaboration with systems engineers, U.S. citizenship, a technical degree or equivalent experience, Secret clearance eligibility, and 10–15% domestic and international travel.

Lead the design and implementation of enterprise data lake architecture for DoW projects. Administer Databricks environments, optimize Delta Lake and ETL pipelines, integrate AI/ML workflows, and develop secure cloud solutions across AWS, Azure, and GCP. Lead technical teams, establish DevSecOps and CI/CD practices, address architecture issues, and coordinate between clients, business analysts, and developers. The role requires TS/SCI clearance and expertise in cloud security, RBAC, compliance, and data governance.

Designs and develops complex cloud-native data solutions, scalable batch and real-time pipelines, APIs, data models, and enterprise data platforms. Implements data governance, quality, lineage, security, observability, CI/CD, automated testing, and operational reporting capabilities. Collaborates with architects, product owners, analysts, governance, security, and platform teams on technology strategy and cloud modernization. Mentors engineers, leads technical design discussions, presents recommendations, and supports AI-ready data products and emerging development tools.

Architect and operate enterprise-scale data platforms supporting cybersecurity operations. Build batch and streaming pipelines, data lakes, warehouses, storage backbones, normalization frameworks, schemas, and telemetry integrations. Optimize scalability, reliability, cost, security, and data quality while enabling SIEM/XDR analytics. Collaborate with security operations, detection engineering, threat management, and data science teams, and maintain architecture documentation and operational runbooks.