Role Purpose

The BI Ops Specialist ensures the continuity, reliability, and quality of the analytical ecosystem for Mexico and LATAM, enabling strategic decision‑making across Marketing, Distribution, and Finance, in integrated collaboration with the Data Strategy team based in LA and London. Operating with high autonomy, this role connects territories, business teams, and data operations to foster a data‑driven, insight‑ready environment—consistent, scalable, and built for continuous improvement.

Key Responsibilities

• Data Operations & Automation
  • Operate and monitor multi‑territory data pipelines to ensure timely, accurate, and stable updates.
  • Proactively detect and resolve anomalies (missing data, ID mismatches, numeric inconsistencies) and drive root‑cause fixes.
  • Implement process automation to reduce manual work, increase reliability, and drive operational efficiency.

• Predictive Models Execution & Innovation
  • Execute notebooks, scripts, and batch processes for training, scoring, and regenerating model outputs; validate integrity and standardize deliverables for business consumption.
  • Innovate and experiment: explore and evaluate new approaches (e.g., neural networks and other ML techniques); perform exploratory data analysis (EDA) and statistical testing on new and existing data sources; and turn findings into scalable features, validation routines, and operating standards.

• Power BI, DAX & Data Visualization
  • Maintain and optimize Power BI assets, including semantic modeling, DAX measures, and data visualization best practices to improve usability and performance.
  • Ensure metric consistency and interpretability across MX & LATAM.

• Business Support & Cross‑Functional Collaboration
  • Prepare and maintain inputs for weekly/regional deliverables to support BI operations and workflows.
  • Meet with partner teams (Marketing, Distribution, and Finance) to capture priorities and translate them into clear data requirements (datasets, queries, dashboards, model inputs) to schedule and deliver the resulting data products that enable processes, analytics, and insights.

• Documentation, Standards & Continuous Improvement
  • Maintain living documentation (processes, naming conventions, data structures, runbooks).
  • Propose improvements that reduce manual steps, increase stability, and raise data quality and discoverability.