Top Data Engineer Jobs in Portugal

Develop, maintain, and optimize scalable data solutions, enterprise ETL processes, and operational data workflows. Design, build, test, automate, and maintain data management systems; develop algorithms, predictive models, and proof-of-concepts; and collaborate with architects, modelers, and IT teams. The role also includes managing projects through delivery, supporting business initiatives, evaluating data solutions, and contributing to internal consulting and digital transformation activities.

Develops and supports ETL workflows, enterprise data warehouses, data marts, and automated data pipelines. Uses Informatica, PL/SQL, and scripting to move data between on-premises systems, Snowflake, Salesforce, and other platforms. Participates in technical design, programming, testing, standards, change control, and 24-hour on-call support. The role requires four days onsite in Lansing, Michigan and may involve ADP I or II clearance and U.S. citizenship.

Designs and builds ETL/ELT pipelines and data architectures across hybrid big-data and traditional database environments. Develops dimensional and normalized data models, ingests structured and unstructured sources, maintains data quality and security, troubleshoots pipeline issues, and delivers analytical reports and dashboards using Cognos and Tableau. Collaborates in agile teams, manages change requests, audits data integrity, and applies testing, documentation, and development best practices.

Builds and maintains ETL/ELT data pipelines and architecture for analytics. Responsibilities include monitoring jobs, troubleshooting loads, managing tickets, discovering and ingesting data from databases, APIs, files, and third-party applications, and transforming structured and unstructured data. The role also performs data modeling, quality audits, software testing, documentation, and agile project delivery while collaborating with technical teams and stakeholders.

Supports data integration development and validation by analyzing ETL processes, verifying data integrity, testing integrations, diagnosing defects, and aligning business requirements with technical solutions. Collaborates with integration developers using Agile methods, follows data security standards for personally identifiable information, and participates in requirements reviews and project planning.

Design and lead scalable, secure, highly available database infrastructure for multi-terabyte SQL Server environments. Set technical direction for data architecture, performance, real-time pipelines, security, and growth. Troubleshoot complex production issues, optimize queries and indexes, guide cross-functional projects, mentor engineers, review changes, reduce technical debt, and evaluate emerging technologies. Monitor database health using Splunk, Datadog, and Grafana while influencing engineering and Site Reliability strategy.

Build and support knowledge graph and data engineering solutions for classified defense and intelligence customers. Work with graph theory, data modeling, graph databases, and query languages to structure complex relationships. Collaborate with software development teams, communicate with analysts and senior stakeholders, and potentially develop training materials. The role requires working onsite in a SCIF and maintaining an active TS/SCI clearance while obtaining a CI polygraph.

Designs and maintains scalable data architectures, batch and real-time ETL/ELT pipelines, data models, storage systems, and governance controls. Optimizes data platforms for performance, reliability, scalability, and cost. Collaborates with architects, analysts, BI specialists, data scientists, and business stakeholders to deliver trusted datasets and technical solutions. The role also evaluates data technologies and supports cloud-based infrastructure, CI/CD, and machine learning data requirements.

Leads large-scale migration from legacy systems to cloud platforms, including data mapping, transformation, validation, cleansing, and reconciliation. Builds MuleSoft APIs and DataWeave transformations for real-time and batch integrations. Supports Salesforce Data 360, document AI, identity resolution, data governance, metadata, lineage, compliance, testing, cutover, and audit readiness in Agile, federally regulated environments.

Owns end-to-end delivery of production data platforms for utility clients, including discovery, architecture, ingestion, transformation, orchestration, governance, quality, deployment, and handover. Uses Databricks, Spark, Python, SQL, and AWS to modernize legacy systems, integrate utility data sources, build observable pipelines, and deliver operator-facing applications. Leads client engagements, manages scope and timelines, supports migrations, and contributes reusable engineering frameworks and reference architectures.

Configure and maintain Adobe Experience Platform and Real-Time CDP data pipelines, XDM schemas, datasets, identity resolution, Profile enablement, segmentation readiness, and destination activation. Validate data quality, troubleshoot ingestion and identity issues, manage sandboxes, and implement privacy, consent, governance, and access controls. Partner with architects, data engineers, consultants, analysts, data scientists, and marketing teams to support reporting, personalization, and machine learning readiness.

Build end-to-end data engineering and data science solutions for robotics and manufacturing data. Responsibilities include designing scalable multimodal data pipelines, creating analytic datasets, applying statistical and machine learning methods, developing MLOps workflows, building APIs and internal tools, and improving data governance, reliability, automation, and production support. The role partners cross-functionally with robotics, manufacturing, software, and data teams.

Design, develop, test, and maintain scalable data pipelines and architectures. Ensure data quality, lineage, governance, and security. Build automated testing/monitoring, optimize storage and query performance, update data models, and support data integration using SQL/NoSQL, cloud, and distributed processing frameworks.

Design and develop scalable data pipelines, data models, schemas, and integrations for a video advertising platform. Collaborate across engineering, define user stories, deliver features using AI-assisted tools, write unit tests, maintain code quality, and support production systems on a rotating schedule. The role requires strong SQL, ETL/ELT, dbt, Airflow, Snowflake, AWS, and data architecture expertise.

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

Leads the enterprise data architecture strategy, designing scalable platforms for secure data exchange, onboarding, discovery, and consumption. Establishes architecture standards, roadmaps, and engineering practices while adopting modern data and AI technologies. Partners with executives and global engineering teams, influences technical decisions, ensures governance and compliance, and mentors teams. The role requires deep expertise in large-scale data platforms, distributed systems, cloud and on-premises environments, and enterprise integration.

Build and operate scalable financial market data infrastructure, including source evaluation, ingestion, cleansing, modeling, real-time and batch processing, quality governance, reconciliation, monitoring, and data services. Develop Flink-based pipelines supporting trading, research, and AI applications. Partner with product, trading, compliance, procurement, and engineering teams to define data contracts, source strategies, and consistent financial data semantics across markets.

Design and build maintainable data pipelines, ETL processes, and data architecture standards. Collaborate with product managers, analysts, and machine learning engineers to translate requirements into automated, scalable solutions. Apply software engineering best practices, asynchronous systems, APIs, streaming, testing, monitoring, and Python and SQL expertise. Help prioritize data initiatives based on business impact and communicate complex technical concepts to technical and non-technical stakeholders.

Designs and delivers scalable data engineering, analytics, automation, AI-enabled solutions, and supply chain applications. Builds Python solutions, Snowflake data pipelines, data models, reporting, and self-service analytics supporting planning, procurement, logistics, forecasting, inventory optimization, and operational decision-making. Partners with business and technical teams to translate requirements into reliable solutions, improve processes, maintain data quality, and provide technical leadership across analytics and data engineering initiatives.

Develops, maintains, tests, and enhances enterprise infrastructure software. Designs and manages cloud infrastructure using OpenStack and comparable platforms, analyzes system performance, supports software and system engineering, automates networks, and addresses cloud security and operations needs. The role requires strong Linux and Python skills, software development experience, technical documentation, requirements analysis, and a TS/SCI clearance with polygraph.

Designs, develops, and maintains Azure-based data platforms, ETL/ELT pipelines, data warehouses, data lakes, and data models. Manages Azure services, databases, networking, security, monitoring, backups, disaster recovery, and performance optimization. Automates operational tasks and supports CI/CD deployments, production incident resolution, technical support, and migration of on-premises systems to Azure. Korean bilingual proficiency is required.

Architect and build high-performance distributed infrastructure for batch and streaming data across global regions. Optimize state management, checkpointing, JVM performance, and exactly-once processing. Develop AI infrastructure including vector indexing, agentic workflows, and real-time data streaming. Own the full software development lifecycle, contribute to shared tooling and SDKs, and mentor engineers through technical leadership and design reviews.

Designs and leads AWS-native data foundations for enterprise AI applications, including knowledge graphs, ontologies, semantic layers, vector indexes, retrieval systems, and LLM grounding datasets. Builds Python and SQL pipelines using AWS services, establishes data models and governance standards, integrates identity-based access controls, and monitors data and retrieval quality. The role also mentors engineers and citizen developers, sets technical direction, and communicates with cross-functional stakeholders.

Designs, develops, and operates production data pipelines and curated, AI-ready data products for AbbVie R&D. Responsibilities include data integration, normalization, modeling, metadata, lineage, quality controls, governance, documentation, knowledge graph publication, and support for RAG and vector-search workflows. The role collaborates with scientists, engineers, architects, data owners, and vendors; provides technical guidance; monitors pipeline reliability; resolves issues; and ensures compliance with data security, GxP, and regulatory standards.

Designs, builds, deploys, and maintains scalable cloud-native data platforms and pipelines in AWS. Supports data acquisition, preparation, database architecture, cloud migration, AI/ML, data science, and business intelligence initiatives. Leads collaborative teams in evaluating data, designing solutions, and managing operational data flows. Requires TS/SCI clearance with polygraph and experience in all-source analysis and data engineering.