Data Engineer Latam

Overview:
**We Are PepsiCo**

Join PepsiCo and dare to transform We are the perfect place for curious people, thinkers and change agents. From leadership to front lines, we're excited about the future and working together to make the world a better place.

Being part of PepsiCo means being part of one of the largest food and beverage companies in the world, with our iconic brands consumed more than a billion times a day in more than 200 countries.

PepsiCo Mexico is one of the most important consumer products companies in the country. Our product portfolio, which includes 22 of the world's most iconic brands, such as Sabritas, Gamesa, Quaker, Pepsi, Gatorade and Sonrics, has been a part of Mexican homes for more than 116 years.

A career at PepsiCo means working in a culture where all people are welcome. Here, you can dare to be you. No matter who you are, where you're from, or who you love, you can always influence the people around you and make a positive impact in the world.

**Know a little more**: PepsiCoJobs

Join PepsiCo, dare to transform.

**Responsibilities**:
**The Opportunity**

A Data Engineer takes on a pivotal role by crafting and sustaining the intricate systems for gathering, storing, and processing data essential for product insights. They specialize in constructing resilient ETL pipelines, ensuring the quality and governance of data crucial for strategic decision-making in the dynamic CPG landscape. Collaborating closely with diverse teams, Data Engineers optimize and monitor data infrastructure tailored to the specific demands of the consumer goods industry. Their adept use of programming skills, cloud platforms, and big data technologies contributes to the creation of tailored, scalable data solutions that drive innovation and efficiency in the CPG sector

**Your Impact**

As an **Data Engineer LATAM** your responsibilities would consist of:
1. Database Management:

- Proficiency in designing, implementing, and maintaining databases.
- Experience with both relational databases (e.g., MySQL, PostgreSQL, SQL Server) and NoSQL databases (e.g., Cosmos DB, MongoDB, Cassandra, Redis).

2. Data Modeling:

- Strong skills in creating effective and efficient data models.
- Knowledge of different data modeling techniques for both structured and unstructured data.

3. ETL (Extract, Transform, Load) Processes:

- Expertise in designing and developing ETL processes to move and transform data between systems.
- Familiarity with ETL tools and frameworks such as Apache NiFi, Talend, or Apache Spark.

4. Big Data Technologies:

- Exposure to big data technologies and frameworks like Apache Hadoop, Apache Spark, and Apache Kafka.
- Experience in working with distributed computing and storage systems.

5. Programming and Scripting:

- Proficiency in programming languages commonly used in data engineering, such as Python, Java, or Scala.
- Ability to write efficient scripts for data processing tasks.

6. Data Warehousing:

- Knowledge of data warehousing concepts and experience with data warehousing solutions (e.g., Azure Synapse, Teradata).

7. Cloud Platforms:

- Experience with cloud platforms such as AWS (a plus), Azure (main platform), or Google Cloud Platform (a plus)
- Ability to design, implement, and optimize data solutions in a cloud environment.

8. Data Quality and Governance:

- Understanding of data quality principles and experience implementing data governance practices.
- Knowledge of tools and processes for data profiling and quality assurance.

9. Collaboration and Communication:

- Effective communication skills to work with cross-functional teams and stakeholders.
- Ability to collaborate with data scientists, analysts, and other members of the organization.

10. Monitoring and Optimization:

- Experience in monitoring and optimizing data pipelines for performance and efficiency.
- Familiarity with tools for monitoring and managing data infrastructure.

11. Version Control and Documentation:

- Proficient in using version control systems (e.g., Git) for code management.
- Thorough documentation practices for code, processes, and data flows.

12. Security:

- Understanding of data security principles and best practices.
- Implementation of security measures to protect sensitive data.

13. Continuous Learning:

- Demonstrated commitment to staying current with industry trends and adopting new technologies.

Qualifications:
**Who Are We Looking For?**

**Education**
- Bachelor's Degree required. Computer Engineering, Actuarial Sciences, Statistics, Computer Science

**Experience**
- 3-5-years experience in Database management and programming capabilities, ETL Processes and Big Data Technologies, Cloud Platforms and Data Warehousing, Programming and Scripting, Collaboration, Monitoring, and Optimization.
- ** English**: 100 % Oral and written
- ** Tools**: Programming capabilities, Statistical and big data software management (SQL, R/ R Studio, Python, Shiny, C#, Advisory) Visualization So