Data Architect

Overall Objective of this role in our Tech Team

Our Data Architect is responsible for designing, building, and optimizing the data architectures necessary to support the operations of Digital@FEMSA for the Credit strategy, ensuring the integrity, availability, and efficiency of data throughout the organization. This role involves closely collaborating with development and business teams to understand their needs and translate them into robust and scalable data solutions. Additionally, the Data Architect will play a key role in promoting best practices in data management and in the adoption of advanced technologies and methodologies, such as microservices architecture, containerization, and test-driven development (TDD, ATDD, BDD). 

 Some Responsaibilities:

1. Design and Develop Data Architectures: Create and maintain scalable, high-performance data architectures that meet the current and future needs of the organization. 
2. Collaboration with Teams: Work closely with development, business, and IT teams to gather requirements, understand business processes, and translate them into effective data models and solutions. 
3. Data Governance and Security: Ensure compliance with data governance and security policies, establishing standards and best practices for data management across the organization. 
4. Optimization and Performance: Continuously optimize and improve data architectures to enhance performance, scalability, and cost-effectiveness. 
5. Data Integration: Oversee data integration processes, ensuring seamless data flow between systems and efficient ETL (Extract, Transform, Load) processes. 
6. Adopt and Implement Advanced Technologies: Lead the adoption of cutting-edge technologies and methodologies, such as microservices, containerization, and test-driven development (TDD). 
7. Data Modeling: Design and implement logical, physical, and conceptual data models to support analytics, reporting, and business intelligence needs. 
8. Data Quality Assurance: Implement data quality frameworks and processes to ensure accuracy, consistency, and completeness of data. 
9. Documentation: Maintain comprehensive documentation of data architectures, models, processes, and integration points. 
10. Stakeholder Communication: Communicate complex data architectures and solutions to non-technical stakeholders, ensuring alignment with business objectives. 
11. Data Strategy: Contribute to the development and execution of the organization's data strategy, aligning it with broader business goals. 
12. Cloud Integration: Lead the integration of cloud-based data solutions, ensuring alignment with the organization's cloud strategy. 
13. Data Warehousing: Design and implement data warehousing solutions to support large-scale data analytics and reporting. 
14. Regulatory Compliance: Ensure that all data solutions comply with relevant regulations and standards, such as GDPR or HIPAA. 
15. Capacity Planning: Plan for future data storage and processing needs, ensuring that the infrastructure can scale with the organization’s growth. 
16. Project Management: Manage data-related projects, ensuring timely delivery, within budget, and meeting quality standards. 
17. Risk Management: Identify and mitigate risks related to data architecture, including potential security threats and data breaches. 

Requirements:

1. Education: Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field. 
2. Experience: 7+ years of experience in data architecture, data engineering, or a related field, with proven expertise in designing and implementing complex data solutions. 
3. Technical Skills: Proficiency in data modeling, database management, ETL processes, and data warehousing. Experience with cloud platforms (AWS, Azure, Google Cloud), big data technologies (Hadoop, Spark), and programming languages (SQL, Python, Java). 
4. Architecture Frameworks: Familiarity with architecture frameworks such as TOGAF, Zachman, or similar. 
5. Analytical Skills: Strong problem-solving abilities and analytical skills, with a focus on data-driven decision-making. 
6. Communication: Excellent verbal and written communication skills, with the ability to translate technical concepts for non-technical stakeholders. 
7. Project Management: Experience in managing complex data projects, including planning, execution, and delivery. 
8. Regulatory Knowledge: Knowledge of relevant data protection regulations and standards. 
9. Advanced English: Advanced proficiency in English, both written and spoken, is required for effective communication in a global environment. 

Digital FEMSA 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. 
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