EY - Data Modeler (5-10 yrs)

Job Description :

- Experience in working with SME's to build Conceptual Data models

- Convert business requirements into technical requirements, supported by an efficient data model and detailed mapping

- Build Logical/Physical Models using best practices to ensure business requirements are met within the agreed SLA's

Hands on experience of implementing the following methodologies :

- Dimensional models (Ralph Kimball)

- Corporate Information Factory (Bill Inmon)

- Data Vault

- Experience of building Data Lake / Data Warehouse on Hadoop

- Optimize logical/physical models to support new requirements

- Optimize logical/physical models with required metadata using Industry standard tools (Preferably ER/Studio)

- Ability to interpret and communicate technical information into business language.

- Must be very strong in pl/sql

- Develop and implement best practices and processes around naming standards to ensure consistency across the models & versioning of models

- Perform reverse engineering of physical models from existing databases and scripts

- Recommend opportunities to reuse existing data models for new use cases

- Analyze challenges around data integration / data mastering/ data migration and propose appropriate solutions

- Work with development team to implement data strategy, build efficient data flows and testing of data loads

- Work with consumption teams to help explain the data model usage and amend the model to support efficient exploitation of data

- Strong SQL and Pl/SQL skills associated with data profiling, data analysis skills

- Work with multiple IT roles, including Data Analysts, Solution Architects and Information Architects, to embed the use of data models and within both project and strategic activities

- Creation, review and maintenance of data modeling and data mapping artefacts

- Contribute to the E2E Data Architecture & Design (Ingestion -> Transformation -> Reporting)

- Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization

Demonstrate foundational knowledge of core data concepts on Azure data platforms :

- Normalization / Denormalization scenarios

- SCD types req. scenarios

- Data validation

- Data prep / cleansing

- ADB

- Identifying and implementing automation where applicable