Director, Data Modeling

Key Skills

Analytical and Problem solving, Apache Hadoop, Data Analytics, Data Modeling, Data science techniques, Database, Design, ETL frameworks, MongoDB, NoSQL, Postgres, PowerBI, Python Programming, Snowflake, SPARK Programming, SQL, Tableau

Job Description

The Director of Data Modeling defines and leads the data modelling framework, governance, and roadmap initiatives to attain the strategic vision for the Company. The successful candidate will work with the strategic requirements of the organization to fulfill business needs, and partner with management to propagate this vision across the enterprise. The Director also provides data modeling expertise throughout the organization in support across Quest’s Data Fabric, Data Mesh, Data Products and traditional data and analytics platforms.

• Develop and maintain conceptual, logical, and physical data models that align with business requirements, data governance standards, and industry best practices.
• Collaborate closely with stakeholders including data scientists, data engineers, and analysts to understand data requirements, identify key entities, relationships, and attributes, and translate them into robust data models.
• Design and implement database schemas, tables, and indexes, ensuring data integrity, performance, and scalability.
• Optimize and enhance existing data models to improve query performance, data storage, and retrieval efficiency.
• Conduct data analysis to identify data quality issues, anomalies, and inconsistencies, and develop strategies for data cleansing and data governance.
• Work closely with data scientists, analysts, and data engineers to integrate data models into data pipelines, data fabric, lakehouses, and analytical applications.
• Provide guidance and mentorship to junior data modelers, sharing best practices, and fostering a collaborative learning environment.
• Stay up to date with emerging trends, technologies, and advancements in data modeling, data management, and database design, and evaluate their potential impact on our organization's data strategy.
• Collaborate with cross-functional teams to define and implement data standards, data policies, and data governance frameworks.
• Participate in data architecture discussions and contribute to the overall data strategy, ensuring alignment with business objectives.
• Provides input into hiring, developing, promotions of D&A staff.
• Coordinate and assist in Data flow design across the function: within sub-capabilities (from System of Record to Analytics applications) 
• Collect and Align Measure and Metric, and associated business rules, design, and management.
• Build and Consolidate Actual data lineage documentation.
• Input into business blueprints and Master Data Design across the supported functions.
• Adoption of Internal and external data standards, especially with regard to Master Data, reference taxonomies/ontologies and data formats.
• Support the development of the Enterprise Data and Analytics strategy and roadmap for aligned function, in line with business and functional strategy and data requirements.
• Evangelize what Data Modeling is and the value and impact of good data design and governance to both HTAS and business teams.
• Establish strong working relationships across HTAS and business groups to develop an in-depth understanding of business priorities and data requirements.

• A Bachelor's or Master’s degree in Computer Science, Information Systems, or a related field.
• Proven experience (15+ years) as a Data Modeler or in a similar role, with a focus on enterprise-level data modeling and database design.
• Strong proficiency in data modeling techniques, such as entity-relationship modeling, dimensional modeling, and normalization.
• Expertise in SQL, Python and experience with relational databases (e.g.,Postgres, Snowflake, Teradata) and database and lakehouse management systems.
• Solid understanding of data integration, data warehousing, ETL and Data Fabric processes.
• Proficiency in data modeling tools (e.g., ERwin,) and data visualization tools (e.g., Tableau, Power BI).
• Experience with big data platforms (e.g., Hadoop, Spark) and NoSQL databases (e.g., MongoDB, Cassandra) is a plus.
• Strong analytical and problem-solving skills, with the ability to analyze complex data requirements and translate them into practical data models.
• Excellent communication and collaboration skills, with the ability to effectively convey technical concepts to non-technical stakeholders.
• Proven ability to work independently and manage multiple projects with competing priorities.