? We’re building our Data Engineering talent team at Intugo!

We’re looking to connect with Data Engineers at different levels of experience, from professionals who are already building and maintaining modern data pipelines to senior engineers ready to take greater ownership of architecture, technical standards and mentoring.

If you enjoy working with data platforms, cloud technologies and solving real-world data challenges, we’d love to hear from you.

About the role As part of a growing technology team, you’ll contribute to the development and evolution of modern data capabilities that support analytics, Machine Learning and AI initiatives.

Depending on your experience and seniority, your responsibilities may include:

- Building and maintaining reliable ETL/ELT data pipelines.
- Transforming raw data into clean, structured and usable datasets.
- Working with cloud data platforms such as BigQuery or equivalent technologies.
- Developing solutions using Python, SQL, dbt and Airflow / Cloud Composer.
- Implementing data quality checks, monitoring and pipeline observability.
- Supporting batch and real-time data processing.
- Collaborating with Data Scientists, Business Analysts, Software Engineers and other technology teams.
- Contributing to data governance, documentation and security practices.

For more senior profiles, the scope may also include data architecture, technical decision-making, MLOps / feature stores, cloud cost optimization, code review and mentoring other Data Engineers.





Requirements We’re open to different levels of experience, so the depth expected in each area will depend on your background.

We’re especially interested in candidates with experience in some of the following:

- Data Engineering and ETL/ELT pipelines in production environments.
- Strong SQL skills.
- Python for data processing and automation.
- Cloud data platforms — ideally GCP, although experience with AWS or Azure is also valuable.
- BigQuery, Snowflake, Redshift, Databricks or similar technologies.
- dbt or comparable data transformation tools.
- Airflow / Cloud Composer or other orchestration platforms.
- Git, code review and CI/CD practices.
- Data quality, monitoring and observability.

Nice to have

- Streaming technologies such as Kafka, Pub/Sub, Dataflow or Spark Streaming.
- Data governance, lineage or catalog tools.
- MLOps or experience supporting Machine Learning environments.
- Experience designing data architectures or mentoring other engineers.

Above all, we value technical curiosity, ownership, collaboration and a pragmatic approach to solving data problems.

Benefits

- Full-time, long-term opportunity.
- Opportunity to participate in strategic technology, data and AI initiatives.
- Collaboration with multidisciplinary technology teams.
- Personalized compensation and benefits offer based on the candidate’s experience, technical background and seniority.
- Additional details regarding the work model and conditions will be shared throughout the process.

📌 AI / Data Engineer (México)
🏢 Intugo México
📍 México