Senior Analyst, Data Modeling

The Senior Analyst, Data Modeling is responsible for both the theory and practice of making RCG a data-driven organization. In this role, the Senior Data Analyst/Modeler will design, develop and manage data solutions for use by internal stakeholders in all areas of RCG including Product Management, Revenue, Sales, Marketing, Digital, to name a few. Working closely with Data Solutions Engineering, he or she will architect data definitions and structure and oversee the ETLs that populate them in order to deliver meaningful, high-quality data to downstream users and platforms, including data scientists, business and product analysts, reporting platforms, and automated processes. Strong experience in requirements engineering and the design, development, and deployment of ETL and Data Modeling. A broad set of skills and knowledge including software, systems and solution development spanning multiple technical domains Strong communication skills including the ability to socialize, influence and gain support for proposed technology and solution architectures from the business and IT community. Technical team leadership, mentorship, and collaboration as well as the ability to cultivate strong working relationships with end-users, peers, and vendors Essential Duties and Responsibilities: Key areas of responsibility in descending order, with the responsibility requiring the most amount of time first. Gather and translate requirements — work directly with business stakeholders to understand what they're trying to decide, and turn that into clear data and reporting requirements. Design logical and conceptual data models — define entities, relationships, grain, and business rules ahead of physical implementation. Analyze and interpret data to be modelled into the enterprise data platform. Define and enforce standards for the data platform. Maintain the semantic layer — define certified metrics and dimensions so the same term means the same thing everywhere it's used. Deliver analysis and insight — run the ad hoc analysis, cohort/trend work, and investigative queries that answer specific business questions. Partner with Data Engineering — hand off logical models with clear documentation, and collaborate on how they get physically implemented and tested. work with Data Engineers on the boundary between raw ingestion and modeled data, and flag upstream data issues early. Define requirements for engineers developing new data pipelines, database infrastructure and instrumentation. Communicate findings — present analysis and recommendations to non-technical stakeholders in a way that drives decisions, not just describes data. Partner with stakeholders — work with product managers, business partners and analysts to understand business rules to understand what the model needs to support, not just what it needs to store. Draw on deep experience with data management and analysis to identify improvements and increase efficiency, reliability, and usability of data across the organization. Define and document the underlying metrics and design robust infrastructure (ETLs, table structures, metadata) to enable consistent reporting on those metrics throughout the organization.