IC6 - Sr Staff Data Engineer

Objective of the Role 

Responsible for leading the continuous improvement of data engineering practices within Spin, ensuring the implementation of robust and scalable architectures that meet the current and future needs of the business. This strategic role involves making critical technical decisions, defining quality standards in data handling and processing, and actively mentoring other engineers to elevate the team's knowledge and operational excellence. Works closely with pods to transform the data engineering culture, improving actual engineering practices, and ensure that data solutions are secure, efficient, and aligned with business objectives.  

Main Responsibilities 

• Lead the design and development of complex data architectures, ensuring that solutions are scalable, maintainable, and aligned with the company's data strategy. 
• Act as a mentor for junior and senior data engineers, providing technical guidance, conducting code reviews, and promoting professional development within the team. 
• Promote and apply best practices in data engineering, including ETL/ELT processes, data modeling, and principles of data architecture such as data quality, governance, and scalability.
• Create and maintain detailed technical documentation on data architectures, designs, and operational procedures.  
• Lead the resolution of complex data engineering issues, ensuring a rapid and effective response and promoting long-lasting solutions.  
• Actively participate in high-level strategic meetings, contributing ideas and technical data solutions that drive the business strategy.  
• Design and implement automation solutions to improve the efficiency of data engineering processes and operations.  
• Promote a culture of collaboration, high performance, diversity, inclusion, and constant respect within the data engineering team. 
• Promote an autonomous work culture by encouraging self-management, accountability, and proactive problem-solving among team members. 
• Serve as a Spin Culture Ambassador to foster and maintain a positive, inclusive, and dynamic work environment that aligns with the company's values and culture. 

Required Knowledge and Experience 

• Minimum 10 years of experience in data engineering or related fields. 
• Mastery of core data engineering concepts and principles, including designing and optimizing complex ETL (Extract, Transform, Load) processes and highly scalable, fault-tolerant data pipelines.  
• Advanced knowledge of dimensional data modeling and advanced techniques in this field, including structured, semi-structured, and unstructured data storage (non-SQL), as well as ETL, ELT construction.  
• Advanced knowledge in data processing: batch, microbatch, near real-time, and real-time.  
• Advanced knowledge in Data Engineering Lifecycle (also known as Data Processing Lifecycle).  
• Advanced knowledge in understanding Architecture: Business, Solutions, Data, etc.  
• Advanced in business vision (business domain), to sensitively identify how data contributes to the business. Advanced mastery and evidence with projects using Databricks Data Platform.  
• Advanced mastery and evidence with projects using the Amazon Web Services (AWS) Stack for Data.  
• Advanced knowledge of file processing concepts, including handling very large datasets and working with various file formats (e.g., CSV, JSON, Parquet, Avro).  
• Expertise in data governance principles, including data quality management, data lineage, data security, and compliance with data privacy regulations (e.g., GDPR, CCPA).  
• Extensive experience with CI/CD pipelines and automation tools for data engineering workflows.  
• Expertise in various data architectures, including data lakes, data warehouses, data marts, and data mesh.  
• Ability to articulate complex technical concepts to non-technical stakeholders and collaborate effectively across teams. 

Spin está comprometida con un lugar de trabajo diverso e inclusivo. 
Somos un empleador que ofrece igualdad de oportunidades y no discrimina por motivos de raza, origen nacional, género, identidad de género, orientación sexual, discapacidad, edad u otra condición legalmente protegida. 
Si desea solicitar una adaptación, notifique a su Reclutador.