Senior Data Engineer (Spark/Kafka/Hadoop) - Hybrid Lisbon (3 days/week office)

Senior Data Engineer (Spark/Kafka/Hadoop) - Hybrid Lisbon (3 days/week office)

ABOUT THE OPPORTUNITY

Join the marketing technology division of a global technology leader. Its platforms power marketing measurement, customer insights and campaign optimization for businesses worldwide. As a Senior Data Engineer, you’ll design, build and operate scalable data platforms and pipelines at enterprise scale. You’ll also influence future-state data architecture and help accelerate an ongoing cloud transformation. This is a 12-month project starting in November 2026.

PROJECT & CONTEXT

• Build batch, streaming and real-time data pipelines for business-critical products in campaign measurement, reporting, customer insights and AI/ML.

• Develop reusable frameworks for data ingestion, transformation, orchestration and delivery across data lake, warehouse and lakehouse environments.

• Support the modernization and cloud migration of legacy platforms toward cloud-native architectures.

• Strengthen data quality, observability, governance, lineage and security across the data ecosystem.

• Mentor engineers, lead root-cause analysis on complex production issues and contribute to architectural decisions and technology roadmaps.

• Work in close partnership with Product, Engineering, Data Science, Analytics and Business stakeholders.

• The work model is hybrid, with 3 days per week on-site in Lisbon and regular working hours. The selection process includes an interview with the client.

WHAT WE’RE LOOKING FOR (Required)

• Extensive experience designing and building scalable data platforms and distributed data processing solutions

• Strong expertise in Apache Spark, Apache Kafka, the Hadoop ecosystem, cloud-native data services and large-scale data processing frameworks

• Proficiency in one or more of the following: Python, Java, Scala or SQL

• Experience developing data pipelines for analytics, reporting, machine learning and operational data products

• Deep understanding of data modeling, ETL/ELT design patterns, data architecture and data lifecycle management

• Experience building and supporting solutions on AWS, Azure or GCP

• Knowledge of data governance, security, privacy, lineage, metadata management and regulatory compliance

• Experience with CI/CD, DevOps automation, Infrastructure-as-Code and observability frameworks

• Proven experience leading technical initiatives, influencing architectural decisions and mentoring engineers

• Strong communication and stakeholder management skills across engineering, product, analytics and business teams