Lead Data Warehouse Modeler

Job Overview:

We are currently hiring on behalf of a reputable client seeking an experienced and highly skilled Lead Data Warehouse (DWH) this role you will be responsible for transforming complex business information into robust data models (conceptual logical and physical) that drive organizational success. You will play a pivotal role in designing solutions that support Enterprise Information Management Business Intelligence Machine Learning and Data Science initiatives. The ideal candidate is an expert in data architecture who can govern standards optimize performance and work collaboratively with cross-functional teams to implement effective data strategies.

Key Responsibilities:

Data Modeling & Architecture:

• Design develop and maintain comprehensive data models for the data warehouse data marts staging areas operational data stores (ODS) and big data platforms.
• Translate business requirements into conceptual logical and physical data models.
• Assist the DBA team in developing physical data models and the implementation of ODS data marts and data lakes.
• Oversee the expansion of existing data architecture and optimize data query performance using industry best practices.

Governance & Standards:

• Define and govern data modeling and design standards tools best practices and related development methodologies across the organization.
• Apply strict Data Naming Standards manage model repositories (check-in/check-out) and document translation decisions.
• Set standards for document naming security protocols and data lifecycle & retention architecture.

Strategy & Implementation:

• Implement business and IT data requirements through new data strategies and designs across all data platforms (relational dimensional) and tools (reporting visualization analytics).
• Identify necessary architecture infrastructure and interfaces to data sources automated data loading tools security frameworks and analytic models.
• Utilize data profiling tools and techniques to develop review and QA data requirements.

Collaboration & Leadership:

• Work proactively and independently to address project requirements articulating issues and challenges to reduce delivery risks.
• Partner with business and application/solution teams to build data flows and implement data strategies.
• Support the development and validation required throughout the DWH and BI systems lifecycle maintaining user connectivity and data security.
• Use facilitation skills to engage Subject Matter Experts (SMEs) and gather necessary requirements.

Qualifications & Requirements:

• Bachelors or masters degree in Computer Science Data Science or a related technical field.
• A minimum of 10 years of hands-on experience in data warehousing data modeling or a related field.
• Proven experience working with dimensionally modeled data Enterprise Data Warehouses and Big Data platforms in multi-data-center contexts.
• Deep understanding of data warehouse modeling skills (conceptual logical and physical design) Operational Data Stores Data Marts and Big Data Platforms.
• Advanced working knowledge of SQL 3rd Normal Form (3NF/OLTP) and Dimensional (OLAP) database design concepts.
• Expert proficiency with metadata management and data modeling tools (e.g. Erwin ER Studio or similar). Experience with Business Intelligence tools (e.g. Power BI) is required.
• Hands-on experience with modeling design configuration installation performance tuning and sandbox Proof of Concepts (POCs).
• Solid working knowledge of database loading methods database platforms and the ability to work within an Agile Development Methodology.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions.

Business & Personal Attributes (Interpersonal):

• Exceptional ability to clearly communicate complex technical ideas to audiences of varying technical capacities. Strong presentation skills are a must.
• Self-directed and capable of working independently as well as collaboratively within a larger team. Demonstrated ability to take ownership of development and maintenance projects.
• Strong decision-making and problem-resolution skills with an intellectual curiosity for finding innovative solutions to data management challenges.
• Ability to quickly learn and adapt modeling methods from case studies or proven approaches. Comfortable supporting the data needs of multiple teams systems and products in a dynamic environment.