• Deeply understand Fever’s backend systems and data models, identifying the logic and transformations that connect business processes to data representations. • Collaborate fluidly with Product Managers, Project Managers, and business stakeholders to translate ideas and reporting needs into clear technical requirements and data structures. • Develop and optimize ETL/ELT workflows using Python, DBT, Airflow, and Snowflake, ensuring scalability, maintainability, and reliability. • Design, build, and maintain partner-facing data products, including APIs (real-time and batch), dashboards, webhooks, and file-based exports. • Ensure that all data delivered to partners is accurate, consistent, and aligned with the underlying business context. • Contribute to the architecture, testing, and observability of our data ecosystem, promoting best practices and automation wherever possible. • Take ownership from idea to delivery — you’ll scope, design, implement, and ship solutions in close collaboration with cross-functional teams. • Support the evolution of Fever’s data mesh, helping domain teams design data products that follow common engineering and governance standards.

We are looking for a Data Engineer responsible for designing, developing, and optimizing data processing solutions, ensuring quality, scalability, and security in software products. This role directly contributes to meeting timelines, scope, and technical standards by applying best practices in data engineering. Responsibilities - Participate in cross-functional meetings to define project objectives and scope. - Analyze and prioritize business requirements related to data. - Design and develop data extraction, transformation, and loading pipelines (ETL/ELT). - Develop applications for extracting data from various sources and formats (JSON, XML, PDF, etc.). - Write clean, efficient, and scalable code, adapting to new technologies as needed. - Implement data quality methodologies throughout ingestion and transformation processes. - Optimize services, queries, and processes to reduce operational costs and improve performance. - Validate the functionality, integrity, and security of data engineering processes.

We are looking for a Data Engineer responsible for designing, developing, and optimizing data processing solutions, ensuring quality, scalability, and security in software products. This role directly contributes to meeting timelines, scope, and technical standards by applying best practices in data engineering. Responsibilities - Participate in cross-functional meetings to define project objectives and scope. - Analyze and prioritize business requirements related to data. - Design and develop data extraction, transformation, and loading pipelines (ETL/ELT). - Develop applications for extracting data from various sources and formats (JSON, XML, PDF, etc.). - Write clean, efficient, and scalable code, adapting to new technologies as needed. - Implement data quality methodologies throughout ingestion and transformation processes. - Optimize services, queries, and processes to reduce operational costs and improve performance. - Validate the functionality, integrity, and security of data engineering processes.

We are looking for a Data Engineer responsible for designing, developing, and optimizing data processing solutions, ensuring quality, scalability, and security in software products. This role directly contributes to meeting timelines, scope, and technical standards by applying best practices in data engineering. Responsibilities - Participate in cross-functional meetings to define project objectives and scope. - Analyze and prioritize business requirements related to data. - Design and develop data extraction, transformation, and loading pipelines (ETL/ELT). - Develop applications for extracting data from various sources and formats (JSON, XML, PDF, etc.). - Write clean, efficient, and scalable code, adapting to new technologies as needed. - Implement data quality methodologies throughout ingestion and transformation processes. - Optimize services, queries, and processes to reduce operational costs and improve performance. - Validate the functionality, integrity, and security of data engineering processes.