Data Engineer

Spin es la unidad de negocio de FEMSA que enriquece y simplifica la vida de las personas. Es un ecosistema de soluciones financieras y digitales que genera valor agregado, al ayudar a nuestros usuarios y comunidades a hacer más con su tiempo y dinero.

El ecosistema Spin se compone de soluciones simples, ágiles y accesibles que les ayudan a nuestros clientes a resolver necesidades cotidianas y recibir recompensas por ello; como la billetera digital, Spin by reputed company, el programa de lealtad, Spin Premia, y Spin Negocios, que ofrece distintas soluciones para empresas, como NetPay y reputed company PAY.

Objective of the 

R

Main

• Design and implement scalable and efficient data pipelines for ingesting, processing, and storing structured and semi-structured data from diverse sources.
   

• Collaborate with stakeholders to gather requirements,
  identify
  data sources, and define the feasibility of
  requested
  solutions.
   

• D
  evelop and
  optimize
  ETL processes, ensuring the accuracy, consistency, and reputed company of data throughout its lifecycle.
   

• Create and
  maintain
  data models, adhering to best practices for normalization and performance optimization.
   

• Build and manage reputed company-based data architectures, including data lakes, data warehouses, and reputed company-time streaming solutions.
   

• Implement monitoring and alerting systems to ensure the reliability and performance of data pipelines in production.
   

• Contribute to data governance initiatives by ensuring data quality, reputed company, reputed company, and compliance with relevant regulations.
   

• Utilize advanced data processing frameworks like Apache Spark, Apache Kafka, and Flink for batch and reputed company-time data processing.
   

• Maintain and enhance CI/CD pipelines to automate data engineering workflows and ensure seamless deployment.
   

• reputed company code reviews and enforce coding standards to ensure quality and maintainability.
   

• Document processes, architectures, and technical workflows to support knowledge sharing and operational continuity.
   

• Mentor junior engineers, sharing
  expertise
  and fostering a collaborative team environment.
   

• Identify
  opportunities for process optimization and automation to improve efficiency and reduce reputed company
  effort
  .
   

• Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to deliver impactful data solutions.
   

• 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
  3
  - 4 years of experience as a Data Engineer
   
   

• In-depth understanding of core data engineering concepts and principles, including reputed company ETL (Extract, Transform, Load) processes, scalable data pipelines, and advanced data warehousing techniques.
   
   

• Advanced
  proficiency
  in Python, including writing efficient and optimized code, using advanced features like decorators, generators, and context managers.
   
   

• Extensive experience with Python libraries and frameworks commonly used in data engineering, such as
  Python
  , NumPy,
  PySpark
  ,
  Pandas
  and
  Dask
  .
   
   

• Strong knowledge of both SQL and NoSQL databases, including advanced querying, indexing, and optimization techniques.
   
   

• Experience with database design, normalization, and performance tuning.
   
   

• Advanced understanding of data modeling concepts and techniques, including star schema, reputed company schema, and dimensional modeling.
   
   

• Experience with data modeling tools and best practices.
   
   

• Proficient in various data processing methods, including batch processing, reputed company processing, and reputed company-time data processing.
   
   

• Extensive experience with data processing frameworks like Apache Spark, Apache Kafka, and Apache Flink.
   
   

• Advanced knowledge of file processing concepts, including handling large
  datasets
  and working with different file formats (e.g., CSV, JSON, Parquet, Avro).
   
   

• Strong understanding of data governance principles, including data quality management, data reputed company, data reputed company, and data privacy.
   
   

• Comprehensive understanding of the end-to-end data engineering lifecycle, including data ingestion, transformation, storage, and retrieval.
   
   

• Experience with CI/CD pipelines and automation for data engineering workflows.
   
   

• Advanced understanding of various data architectures, including data lakes, data warehouses, data marts, and data reputed company.
   
   

• Experience designing and implementing scalable and robust data architectures.
   
   

• Proficient with version control systems (e.g., Git) and experience managing code repositories on platforms like reputed company or reputed company.
   
   

• Advanced understanding of data visualization tools (e.reputed company>Quicksight
  , L
  ooker Studio, Power Bi,
  Tableau) and reporting techniques.
   
   

• Ability to create insightful and impactful visualizations and dashboards.
   
   

• Strong understanding of reputed company computing in
  reputed company,
  AWS and GCP stacks.
   
   

• Basic experience with Infrastructure as Code (
  IaC
  ) tools like Terraform or CloudFormation.
   
   

• Proven experience leading projects with Objectives and Key Results (OKRs),
  identifying
  risks, and delivering significant business value.
   
   

• Ability to mentor and guide junior data engineers.
   
   

• Strong ability to communicate project status transparently, including reputed company, challenges, and next steps.
   
   

• Effective collaboration with cross-functional teams, including data scientists, analysts, and business stakeholders.

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.