Lead Data Engineer

Process structured and unstructured data into a form suitable for analysis and reporting in analytics and machine learning environments. Leverage Databricks features to operationalize data science models and products in a cluster-computing environment to understand requirements and develop appropriate feature engineering to deliver high performing models. Enhance Feature Store current capability. Create a full machine Learning best practice for model management using MLflow, model assessment through experiment registration, model production promotion via Unity Catalog. Build data pipeline frameworks to automate high-volume and real-time data delivery. Create workflows and delta live tables to maintain batch and stream processes. Implement Dashboard suite dedicated to internal model QA process. Containerize and deploy models at scale in an AWS environment to support third party request. Leverage retool low code, components-based building platform to fast-track the deployment of fully scalable application support to Media Group and clients. Create git-version controlled applications through lower and prod environments. Provide clear data engineering technical leadership, mentoring, and best practices for data management and quality within and across teams. Manage projects, vendors, partners, and contractors as needed. Partner with various NBCU Technology teams in the design and execution of an overall Corporate Data Syndication Strategy for the current Data Mart. Improve automation of various processes in a distributed computing environment, recommend schema improvements, and help adjust queries and jobs orchestration. This position has been designated as hybrid, generally contributing from the office, in New York, NY, a minimum of three days per week.