About the Job:

We are seeking an experienced and skilled Data Engineer to join our dynamic data team. The idóneo candidate should have a strong background in building efficient and scalable data pipelines, designing robust data architectures, and implementing ETL/ELT processes. The role requires proficiency in T-SQL, PySpark, Python, Azure Synapse Analytics, and SSIS.

The Data Engineer will play a critical role in ensuring the availability, integrity, and reliability of our data assets, contributing to the success of our data-driven initiatives.

Responsibilities:
- Design, develop, and maintain end-to-end data pipelines, ensuring smooth and efficient data flow from various source systems to target destinations.
- Collaborate with cross-functional teams to gather requirements, understand data needs, and implement data solutions that align with business objectives.
- Build and optimize data architectures for storing, processing, and analyzing large volumes of structured and unstructured data.
- Implement robust ETL/ELT processes to transform raw data into clean, usable formats,



addressing data quality and consistency concerns.
- Work with data stakeholders to define data integration and transformation requirements, and translate them into technical solutions.
- Develop and maintain documentation for data pipelines, data models, and architectural designs, ensuring knowledge sharing across the team.
- Monitor and troubleshoot data pipelines, addressing performance bottlenecks, data quality issues, and ensuring data accuracy.
- Collaborate with the data infrastructure team to ensure data security, compliance, and privacy standards are upheld.
- Stay up-to-date with industry best practices, emerging technologies, and trends in data engineering, contributing insights to the team's continuous improvement efforts.

Qualifications:
- Bachelor's degree in Computer Science, Information Technology, or a related field. Master's degree is a plus.
- 6+ years of proven experience

📌 Data Engineer (México)
🏢 Tential Solutions
📍 México