Project overview: The Advanced Analytics team delivers long-term value across the company by building custom data products and analytical models, primarily using Machine Learning, but also a range of advanced analytics techniques. Our work enhances business capabilities and integrates directly with operational systems. We follow Agile development, use LEAN tools for change management, and rely on an MLOps environment to ensure scalable, production-ready solutions.
- Responsibilities: Design and implement scalable data pipelines (batch and streaming)
- Collaborate with Data Scientists and ML Engineers to support model development and retraining
- Ingest data into the Data Lake using GCP-native tools
- Build and maintain ETL/ELT processes and unified data models
- Continuously test and optimize data workflows




- Promote a data-driven culture with a focus on reliability and scalability
- 4+ years as a Data Engineer or Software Engineer
- Experience with GenAI projects
- Strong Python and SQL skills
- Experience working in UNIX environments
- Hands-on experience with GCP, especially its data tools (e.g., BigQuery, Dataflow, Pub/Sub, Cloud Storage, Composer)
- Experience with CI/CD pipelines and Docker
- Solid understanding of data structures and distributed processing
- Experience testing and debugging data pipelines
- Nice to have: Experience with Terraform
- Experience with API development
- Stream processing tools (e.g., Apache Beam, Kafka)
- Exposure to MLOps workflows and tools

📌 Data Engineer with Genai Expertise (Monterrey)
🏢 DataArt
📍 Monterrey