Chief Data Officer
The Chief Data Officer (CDO) is responsible for the design, development, deployment, maintenance, enhancement and support of hardware/software for structuring/organizing, storing, retrieving, analyzing, and reporting strategic enterprise information and operational/production data. This includes data for Decision Support, Business Intelligence, Customer Relationship Management, Data Warehousing, Meta-data Repositories, Operational Data Stores, and Enterprise Storage Management. May be responsible for the DBAs who perform physical design, modeling, and administration of operational databases. The incumbent in this role provides vision and strategy for all data management activities. He/She is a champion for data management, governance, quality and vendor relationships across the enterprise. The CDO oversees the enterprise information management (EIM) program, data scientists, and data service providers.
ESSENTIAL JOB DUTIES/RESPONSIBILITIES:
- Establishes Policies and Standards: Establishes data policies, standards, organization and enforcement of EIM concepts. Creates and oversees reports on data metrics and has executive-level responsibility for all enterprise information/data management budgeting and initiatives.
- Manages Data Governance: Organizes and implements policies, procedures, structures, roles and responsibilities that outline and enforce rules of engagement, decision rights and the accountabilities for the effective management of information assets.
- Studies and Maximizes Data Quality: Determines the company’s current data quality and maturity levels – of which there are five. Uncertainty, Awakening, Enlightenment, Wisdom and Certainty.
- Establishes Standards: Establishes enterprise standards – including a uniform and repeatable system development lifecycle methodology.
- Masters Business Intelligence: Establishes an architecture and a collection of integrated decision-support applications and databases – providing the business community easy access to business data.
- Explores Data Warehousing: Creates strategy to provide consistent, clean and integrated data which will be used by Chen Executive team to make more informed decisions.
- Masters Data Management leveraging tools to implement how you capture, integrate and share that MDM information.
- Embraces Enterprise Data Modeling: Delivers value by discovering and resolving data discrepancies among different views and implementations of the same data.
- Explores Metadata Management: Captures the right types of metadata – such as business names, definitions and valid domain values; or perhaps ownership (CFO, HR); or security settings (public, company confidential, HR only, senior management only).
- Navigates Unstructured and Big Data: Includes social media, emails, medical records, pictures, videos and sensor data like RFID. Takes inventory of all that unstructured data – the big data challenge – determining its format, security, ownership and quality. The result could be new storage needs. Determines which unstructured data should – and shouldn’t – be captured.
- Weighs Data in the Cloud: Weighs variables like privacy, security, compliance, ownership and performance questions tied to cloud storage.
- Establishes Business Performance Metrics: Builds business performance dashboards – a business performance management system. Provides timely information and insights that enable employees to improve decisions, optimize processes and plans and work proactively.
- Maintains Security and Privacy: Determines and enforces specific security and privacy requirements for each piece of data – especially as it relates to privacy laws, industry regulations and corporate compliance mandates.
- Develops Intellectual Capital: Including policies and procedures that can be shared in training materials; glossaries; name and contact rosters; and even gathering information from employees’ heads to deal with day-to-day problems and more.
- Performs other related duties as assigned and modified at leader’s discretion.
KNOWLEDGE, SKILLS AND ABILITIES:
- High business acumen and insight.
- Ability to think strategically and drive transformation in a federated operating culture.
- Ability to discern and develop policies and standards and achieve buy-in and adoption.
- Self-driven, motivated to excel, ability to work with minimal supervision and maintain productivity in a fast-paced and, at times, high-pressure environment.
- Ability to work in an ever-changing and sometimes ambiguous environment, identifying key priorities and driving innovative solutions.
- Highly advanced data management knowledge.
- Excellent interpersonal, communication, strategic thinking, and decision-making skills.
- Successful track record of effectively managing relationships with senior executive stakeholders.
- Successful track record of leading and successfully implementing large scale change and innovation initiatives related to data.
- Proficient in Microsoft Office Suite products including Word, Excel, PowerPoint and Outlook.
- Able to travel locally, regionally, nationally up to 50% of the time.
- Fluent in English.
- This position requires use and exercise of independent judgment.
Additional Job Description
EDUCATION AND EXPERIENCE CREDENTIALS:
- Bachelor’s degree in Information Technology, Computer Science or a related field OR significant college-level coursework and at least fifteen (15) years of experience working in data management, including creating partnerships, implementing data governance and understanding the underlying technologies needed to enable data innovation across a large organization required.
- A minimum of 8 years of management level experience required.
- 8+ years’ experience in an executive-level data strategy related role desired.
- Experience implementing or managing a data warehouse on an enterprise-wide scale.
- Proven track record and experience in developing data strategy, policies and procedures, as well as successfully executing programs that meet or exceed expectations in a dynamic environment.
- Experience creating tools and capabilities to assist with data discovery & collaboration, ensure data quality, and to load, clean, enrich, manage and share data from a variety of sources.