Data Engineer

GuestWorld

. Contribute to defining and implementing the data strategy and related governance policies, ensuring the quality, security, consistency, and compliance of information .

Posted 11/3/2026full-timeLisboa • PortugalMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering, focusing on data architecture, governance, and the implementation of data solutions. Proficient in developing scalable data pipelines and ensuring data quality, security, and compliance with regulations such as GDPR.

Highest-signal resume keywords

Data Engineering ExperienceData Architecture KnowledgeSQL and Python ProficiencyData Governance ExpertiseAgile Methodologies Familiarity

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IngestionData TransformationData ModelingPipeline DevelopmentDataOps ImplementationContinuous IntegrationContinuous DeliveryMetadata ManagementMaster Data ManagementDistributed Processing

Soft Skills

Strong CommunicationCollaboration SkillsAnalytical MindsetStructured ThinkingProblem-Solving Ability

Tools & Technologies

DatabricksSparkAzure SynapseMicrosoft Fabric

Industry Keywords

Data LakesData WarehousesLakehousesData QualityGDPR Compliance

Tech Stack

Tools & technologies

AzurePySparkPythonSparkSQL

About the role

Key responsibilities & impact

Contribute to defining and implementing the data strategy and related governance policies, ensuring the quality, security, consistency, and compliance of information
Design, implement, and evolve data architectures and models, ensuring scalability, performance, and alignment with business needs and the technology architecture
Develop and maintain data ingestion, transformation, and delivery pipelines, promoting process automation, reusability, and efficiency
Implement data engineering solutions and frameworks, ensuring the integration of different information sources and the availability of data for analytical use
Ensure metadata management, data cataloging, quality, and traceability, promoting the consistency and reliability of information
Implement DataOps and continuous integration and delivery practices, ensuring the monitoring, maintenance, and optimization of data platforms and solutions
Collaborate with technical and business teams, promoting best practices for managing and using information and the continuous improvement of data solutions

Requirements

What you’ll need

At least 3 years of experience in data engineering, with a broad understanding of architecture and governance
Knowledge of modern data architectures, particularly Data Lakes, Data Warehouses, and Lakehouses, as well as distributed processing platforms (Databricks, Spark, Azure Synapse, or Microsoft Fabric)
Experience developing data solutions using SQL and programming languages such as Python and PySpark
Knowledge of data ingestion and transformation frameworks, data modeling, and pipeline development
Knowledge of Data Governance, data quality, metadata management, and Master Data Management practices
Experience with Agile methodologies and DataOps/DevSecOps practices, including CI/CD, automation, version control, and monitoring
Knowledge of security, privacy, and compliance requirements applicable to data management, particularly GDPR
Analytical mindset, structured thinking, and the ability to solve complex problems, with a strong focus on quality
Strong communication and collaboration skills when working with technical teams and business functions, demonstrating autonomy, initiative, organization, and a focus on innovation and continuous improvement

Benefits

Comp & perks

Competitive salary and benefits package
Ongoing training and relevant certifications
Opportunities for career growth and professional development
Dynamic and collaborative work environment
Growing company with a promising future