**Position Overview**:
**Function Related Activities/Key Responsibilities**:
Optimizing and expanding data pipeline and data flow. Translating business needs into accurate technical specifications. Collaborating in the software design and development of analytical products using Azure Data Services. Contributing to the design and development of data-pipelines, building semantic models, and marts/cubes. Ensuring the architectural integrity of our platform while supporting our software developers, database architects, data analysts, and data scientists on data initiatives.
**Requirements**:
- University Degree or close to graduating (last semester)
- 1 year data engineering related work experience.
- Good understanding of cloud service models: PaaS, IaaS, SaaS.
- Good working knowledge of SQL and database concepts
- Polyglot development: Capable of developing in at least one programming language like Python, Java, or Scala.
- Experience in data modeling techniques and data structures
**Desired Qualifications**:
- Experience with DevOps and CI/CD pipelines for deploying services using Github Actions
- Experience with Big Data migrations/transformations programs in the Data Warehousing / Business Intelligence areas.
- Experience working with public clouds like Azure, AWS etc.
- Azure Certifications:
- AZ-900: Microsoft Azure Fundamentals
- DP-200: Implementing an Azure Data Solution
- DP-201: Designing an Azure Data Solution
- or others related to the position.
- Working knowledge of message queuing, stream processing,



and highly scalable 'big data' data stores.
**Functional Skills**:
- Expertise in SQL and Other Databases: Data engineers need to be comfortable writing SQL queries and managing relational and non-relational databases.
- Knowledge of Cloud Platforms: Experience with platforms like AWS, Google Cloud, or Microsoft Azure is often a must-have for modern data engineering roles.
- ETL Development: Ability to design, build and maintain ETL pipelines.
- Data Warehousing: Understanding of concepts such as data staging, ETL, data marts, and star schema.
**Soft** Skills**:
- Problem-Solving: Ability to troubleshoot and resolve complex data-related issues.
- Communication: Proficient in clearly articulating complex ideas to both technical and non-technical team members and stakeholders.
- Teamwork: The ability to collaborate efficiently with a diverse team of professionals.
- Attention to Detail: Data engineering requires meticulousness to identify slight changes or errors in large amounts of data.
- Time Management: Skill to effectively juggle multiple tasks and deadlines without compromising the quality of work.
- Adaptability: Capacity to adjust quickly to changes in technology, tools and industry standards.
- Continuous Learning: Eagerness to stay updated on the latest technological developments and implement new learnings.
**Skills**:
Cloud Based Services; Software Development; Big Data; Data Solutions; Data Services; Data Pipelines; Data Flows; Data Engineering

📌 Junior Data Engineer (Tláhuac)
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📍 Tláhuac