Director, Data Modeling

Fidelity will not provide immigration sponsorship for this position.

Job Description:

Position Description:

Oversees data lineage, metadata management, and semantic consistency across domains. Establishes and enforces scalable, enterprise-wide modeling methodologies that ensure consistency, quality, and compliance across all data domains. Drives adoption of best practices for conceptual, logical, and physical data models across transactional, analytical, and cloud-native platforms. Influences data architecture decisions to support scalability, interoperability, and business agility. Leads the design of complex data models for multi-platform environments (Snowflake, Oracle, and AWS). Partners with engineering and governance teams to validate that models meet enterprise standards for data quality, accessibility, security, and regulatory alignment.

Primary Responsibilities:

• Translates and incorporates business vision and strategy to data architectural strategy recommendations at the functional level.

• Participates in high-level, cross-functional data architecture design teams.

• Identifies and consults with internal and external technical resources to produce cross-company strategic designs.

• Consults on development and delivery of major technology initiatives for the business unit.

• Consults on deployment of major project deliverables.

• Consults on the documentation of major technology applications.

• Oversees the technical implementation of cross-divisional or company data architectural components.

• Initiates and drives project or strategy discussions with users or external groups to resolve issues.

• Sets vision, goals, and direction of team/organization.

• Plans and leads organization-wide initiatives.

• Provides leadership, technical supervision, and expertise to multiple teams in broad technical areas on complex organization-wide projects.

• Advises senior management on technical strategy.

• Researches and recommends new technologies.

• Works across groups to identify opportunities for organization-wide technology initiatives.

• Regularly provides guidance, training, and coaching to other team members for performance and career development.

• Identifies and plans for future resource needs.

• Determines technical approaches at a strategic level for the business unit.

• Advises on risk assessment and risk management strategies for projects.

• Demonstrated Expertise creating enterprise data lakes used for analytics, Artificial Intelligence (AI), and Machine Learning (ML) capabilities on Cloud and On-Prem Platforms, using big data processing techniques and solutions.

• Demonstrated Expertise designing complex dimensional and relational databases using Ralph Kimball (Star and Snowflake), Bill Inmon Data Vault Design, and Denormalized Analytical Based Table/View data modeling techniques to create conceptual, logical, and physical models according to standards, taxonomy, and best practices, using data modeling tools - Erwin, and SAP Power Designer in an analytics data warehouse environment in Snowflake, Oracle, and SQL Server.

• Demonstrated Expertise building source-to-target mapping documents, profiling, mining, specifying, extracting, cleansing, and analyzing large data warehouses, using SQL Developer, Toad, and Python; generating insights for business and end users using SQL reports; writing SQL/PL-SQL queries and views against the database (SQL Server/Oracle) and generating reports; and modifying the existing SQL queries for improving query performance.

• Demonstrated Expertise generating DDL scripts (Forward-engineer) and DML scripts to create and update physical databases; and performing reverse-engineering of system database to create additional external tables and columns to gather data requirements from the source databases.