Sr. Data Modeler/Analyst at The Ohio State University
Posting DateDecember 8, 2016
Location of Position
For 144 years, The Ohio State University's campus in Columbus has been the stage for academic achievement and a laboratory for innovation. It's where friendships are forged. It's where rivalries and revelry are born.
The university's main campus is one of America's largest and most comprehensive. As Ohio's best and one of the nation's top-20 public universities, Ohio State is further recognized by a top-rated academic medical center and a premier cancer hospital and research center. As a land-grant university, Ohio State has a physical presence throughout the state, with campuses and research centers located around Ohio.
Duties and Responsibilities
The Data Modeler/Analyst will be a part of the Data Warehouse project team, part of a larger team implementing multi-tenant cloud ERP solution to meet the financial management needs of the university, health system, and other entities. They will be focusing primarily on translating various business and technical requirements into workable and understandable data requirements to populate a data warehouse environment in an efficient manner, then working with a Data Movement/ETL Developer to build out the requirements using chosen technologies. This person will work with business analysts, SMEs, Data Movement/ETL developers, BI developers, and other on the project team. The successful candidate must be able to efficiently make investment decisions on data modeling and design that simplify disparate processes and allow optimal retrieval of important data through reporting and analytics. These data will live in a modern data warehouse environment that complements the functionality of the ERP, which possesses robust operational reporting and analytics capabilities. The successful candidate can critically evaluate information gathered from multiple sources, reconcile conflicts, and understand the flow of data, relevant business processes driving the data needs, and technical interfaces that must be created or will be impacted. It is expected that the candidate can document and communicate their work to business users, analysts, data leadership, and project leadership in an efficient manner, using audience-appropriate techniques. They understand the business needs of users of the reports and analytics built on top of the data they’re creating, and how/when users will be accessing and exploring them, and design data that result in optimal user experience in a cost effective manner. A “just enough” data modeling approach is ideal. They can demonstrate reliable data quality in data design, and proven methods to ensure quality throughout the project, ensuring that data is secured through necessary encryption, masking, etc. as necessary. They may also help the team choose tools, technologies, and standards. he successful candidate is an excellent communicator, critical thinker, motivated with a positive attitude; possesses strong verbal, written, presentation and interpersonal skills; and able to work independently to gather and evaluate data.
Master’s degree; working with large data sets, readying data for modern BI/visualization platforms (Tableau, QlikView), columnar databases, data caching technologies, virtualizing multiple data sources without physically moving and modeling data; archival of multiple disparate historical data sources, some of them very large; data virtualization such as Denodo, Cisco Data Virtualization, Informatica; work with various aspects of the Hadoop ecosystem including Spark, MapReduce, Hive, Pig to enable early data exploration; work with R or Python to enable data science for business techniques; work with WSO2, MuleSoft, Dell Boomi, and/or other integration tools; participant in a move from a legacy data warehouse environment built on single row-based database, single source BI tool, and strict star schema to a multi-modal data warehouse leveraging columnar in-memory databases, BI tools supporting multiple data sources, multiple modeling techniques, and support of unstructured and semi-structured data; work with finance data; work in higher education and/or health care; participation on a Workday implementation.
Bachelor’s degree in computer & information science or an equivalent combination of education and experience; 6-8 years related experience working on data warehouse environment (warehouse, associated marts, related disparate data sources) at a large organization; data modeling and analysis, a portion of which must include major ERP solutions; actively participating in a cross-functional team of business and technology staff, full-time and consultants; working with data that are consumed by an entire enterprise, ensuring quality, scalability, and performance; communicating technical work to other team members from business, integration, data conversion, change management, etc.; demonstrating the ability to understand multiple methods for making data available to BI layer, e.g., star schema, data lakes, data virtualization, based on relative value of business need; minimum of 3 years’ demonstrating significant experience in merging of many data sources to satisfy business requirements; data cleansing, data integration, data flow design, and participation in a larger data and reports governance initiative; making concise decisions using considerable independence and initiative, as well as the ability to collaborate in a group setting; ability to work collaboratively with individuals from a variety of different backgrounds.
Application deadline: December 25, 2016.
The Ohio State University is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation or gender identity, national origin, disability status, or protected veteran status.