Sr. Director, Data Solutions

The Sr. Director, Data Solutions is responsible for all aspects of data governance, including developing the overall data architecture strategy and creating and maintaining standards and best practices for data provisioning and data integration. The role acts as the subject matter expert within the organization and is able to liaise with technical staff, directors, product development team, and marketing managers to ensure data goals and objectives are met.   The Sr. Director, Data Solutions uses expert specialist skills and knowledge to define and deliver data solutions and to contribute to the development and implementation of data technology plans in line with the overall strategy of the business and GTS; to act as Lead Architect on major data programs.   Responsibilities:  Lead the data design of solutions for large programs; through expert knowledge translate high-level business requirements into data models and appropriate metadata, test data, and data quality standards Lead the design, development, implementation and maintenance of complex data solutions. Direct and control specialist teams to undertake the delivery of a comprehensive data-centric project, including the following Develop conceptual, logical, and physical data models to support data analysis and business intelligence Create and maintain current- and target-state data architectures Define and manage standards, guidelines, and processes to ensure data quality Manage senior business stakeholders to secure strong engagement for the solution and ensure that the delivery of the project aligns to longer-term strategic roadmaps Work closely with PMO team, governing and shaping the delivery of projects. Work closely with external suppliers to ensure solution makes best use of technology and meets requirements Simplify the existing data architecture, delivering reusable services and cost saving opportunities in line with the policies and standards of the group Provide clear, continuous, and consistent data architecture leadership at a detailed level within the project Lead data vendor selection process, evaluating usefulness and cost of products and making appropriate recommendations Develop conceptual, logical and physical data models to support data analysis and business intelligence Create and maintain current- and target-state data architectures Define and manage standards, guidelines and processes to ensure data quality Oversee end-to-end data life cycle management activities Audits security precautions to ensure adequate protection is in place Implements principles, policies, standards, and guidelines for data management Become a data and analytics evangelist. This role will promote the available data and analytics capabilities and expertise to business unit leaders and educate them in leveraging these capabilities in achieving their business goals.  Skills:   Technical and Business Knowledge/Skills: Foundational knowledge of Data Management practices – Strong experience with various Data Management architectures like Data Warehouse, Data Lake, Data Hub and the supporting processes like Data Integration, Governance, Metadata Management Strong ability to design, build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management. Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies. These should include ETL/ELT, data replication/CDC, message-oriented data movement, API design and access and upcoming data ingestion and integration technologies such as stream data integration, CEP and data virtualization. Applies knowledge of systems, data, and customer requirements to uncover problems and recommends solutions Must have a thorough understanding of the various legislative acts and how they impact data Ability to relate architectural decisions and recommendations to business needs Entity Relationship modeling, metadata systems, data quality tools and techniques BI and reporting (Tableau, Adobe Analytics, Google Analytics etc.) Omeda product knowledge is a strong plus. UML (Use case and class models) Experience in data warehousing, data modeling and/or data analysis Experience with database technologies (e.g., SQL, NoSQL, Oracle, Snowflake) Ability to regularly learn and adopt new technology Strong analytical and problem-solving skills Interpersonal Skills and Characteristics: Strong experience supporting and working with cross-functional teams in a dynamic business environment. Required to be highly creative and collaborative. An ideal candidate would be expected to collaborate with both the business and Technology teams to define the business problem, refine the requirements, and design and develop data deliverables accordingly. Required to have the accessibility and ability to interface with, and gain the respect of, stakeholders at all levels and roles within the company. Is a confident, energetic self-starter, with strong interpersonal skills. Has good judgment, a sense of urgency and has demonstrated commitment to high standards of ethics, regulatory compliance, customer service and business integrity.  Qualifications: At least seven years or more of work experience in data management disciplines including data integration, modeling, optimization and data quality, and/or other areas directly relevant to data engineering responsibilities and tasks. At least five years of experience working in cross-functional teams and collaborating with business stakeholders in support of a multi-departmental data management and analytics initiative. A bachelor's or master's degree in computer science, statistics, applied mathematics, data management, information systems, information science or a related quantitative field Certifications in data architecture, data engineering or other data technologies

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