• Desenvolver e manter pipelines de dados usando Apache Spark e Apache Airflow • Construir e melhorar integrações entre diferentes fontes de dados corporativas • Implementar transformações de dados seguindo as melhores práticas de engenharia e padrões de observabilidade • Suportar a manutenção e otimização de ambientes que rodam em containers e Kubernetes • Suportar o desenvolvimento e manutenção de modelos analíticos utilizados pelo Power BI e Metabase. • Colaborar com Engenheiros de Análise para fornecer ativos de dados confiáveis e bem documentados para equipes de negócios. • Contribuir para iniciativas de catalogação de dados, documentação e governança de dados. • Participar da evolução de agentes de AI utilizados pela equipe de Dados.

• Develop, implement and optimize scalable data pipelines for reliable and secure data flows • Model and transform data according to modern best practices • Develop and operate ETL and ELT processes as well as orchestrated data pipelines • Work with modern cloud technologies, preferably AWS, and support the expansion of our Cloud Data Platform • Analyze and optimize data processes with respect to performance, scalability, stability and data quality • Work closely with data scientists, analysts, product teams and developers

• Contributing to a high-scale, complex product and seeing the real-time impact of your work

• Build scalable, reliable data systems while maintaining SLOs for business-critical pipelines. • Partner with other internal teams such as Product, Sales Ops, and Finance to deliver high-impact data solutions. • Support self-service tooling and a data-driven culture across Pantheon's teams. • Contribute to the technical strategy and operations of Pantheon's data platform. • Stay up-to-date with industry trends and technologies in data engineering, analytics, and modern data platforms. • Continuously improve our standard of engineering excellence by implementing best practices for data architecture, testing, pipeline reliability, and documentation.