Data Governance Manager

Job Description

Companies compile different kinds of data in the form of Master Data (customers, products, branches, brokers, partners, etc.), Transaction Data (payments, purchases, claims, etc.), Reference Data (locations, market information, fund information, currency exchange, etc.), Metadata (metrics, calculation formulas, units and definitions of a data entity), Analytical Data (data residing within a data warehouse, data marts), Documents and Content (claim forms, medical images, maps, video files), and new forms of Big Data. Delegating the use ofstructured and unstructured data, the goal of the Data Governance Manager should be coordinating this information across departments and deciding which information could be best utilized as an asset for the company. Key aspects of data governance include decision making authority, compliance monitoring, policies and standards, data inventories, full lifecycle data management, content management, records management, preservation, data quality, data classification, data security and access, data risk management, and data valuation. Data Governance Manager is essentially a team leader who is serving as a liaison between both internal and external technical and business groups, the Data Governance Manager should bring positive results from their governance of the methods used by data stewards/owners and scientists handling data. 

Responsibilities

• The implementation and oversight of the Company’s data management goals, standards,practices, process, and technologies.
• Being a communicator that is in charge of organizing and streamlining the process with which data is collected, shared, utilized, protected, cleaned, and stored.
• Improving the data quality and managing the protection of sensitive data and information assets.
• Serving as a point of escalation for governance, data quality and protection issues and will work closely with business and functional area leadership to improve the quality and value of core data assets.
• All the while maintaining efficiency and saving the company from inaccurate data handling, unusable data, and potentially saving lots of time and efforts by keeping the data congruent with the company goal.
• Orchestrating teams to organize data available to their business.
• Improving data security and decreasing the risk of regulatory fines.
• Managing efficiency in people, processes, and technology to enable an organization to utilize different kinds of data.