Teams at MUTT DATA

Build and operate production machine learning and data pipelines on Databricks. Responsibilities include orchestrating Jobs workflows, managing Databricks Asset Bundle deployments across environments and countries, administering MLflow and Unity Catalog model lifecycles, monitoring compute costs and observability, and diagnosing runtime incidents. The role requires advanced Python, SQL, Delta, Unity Catalog, CI/CD, Azure DevOps, Git, infrastructure as code, and Databricks platform expertise.

Build and optimize batch and streaming data pipelines, semantic models, and transformations on Databricks using Python and Spark. Define data contracts, quality rules, and data SLOs; guide domain teams on data modeling and product boundaries; mentor engineers and analysts; and improve reusable platform templates, tooling, and engineering practices.

Build and govern scalable machine learning features and AI solutions using Databricks and Unity Catalog. Responsibilities include feature engineering, metadata and lineage management, data governance, CI/CD deployment pipelines, job monitoring, FinOps, and maintaining consistency between training and production environments. The role requires advanced SQL and Python skills, strong data engineering expertise, and knowledge of data quality and scalable architecture practices.