IC6 - Sr Staff Data Engineer

Main

• 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

• 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.