Data Modeller

Responsibilities

Participate in requirements definition, analysis, and the design of logical and physical data models for Dimensional Data Model, NoSQL, or Graph Data Model; Lead data discovery discussions with Business in JAD sessions and map the business requirements to logical and physical data modeling solutions; Conduct data model reviews with project team members; Capture technical metadata through data modeling tools; Ensure database designs efficiently support BI and end user requirements; Drive continual improvement and enhancement of existing systems; Collaborate with ETL/Data Engineering teams to create data process pipelines for data ingestion and transformation; Collaborate with Data Architects for data model management, documentation, and version control; Maintain expertise and proficiency in the various application areas; Maintain current knowledge of industry trends and standards

Requirements

Strong data analysis and data profiling skills; Strong conceptual, logical, and physical data modeling for VLDB Data Warehouse and Graph DB; Hands-on experience with modeling tools such as ERWIN or another industry-standard tool; Fluent in both normalized and dimensional model disciplines and techniques; Minimum of 3 years' experience in Oracle Database; Hands-on experience with Oracle SQL, PL/SQL, or Cypher; Exposure to Databricks Spark, Delta Technologies, Informatica ETL, or other industry-leading tools; Good knowledge or experience with AWS Redshift and Graph DB design and management; Working knowledge of AWS Cloud technologies, mainly on the services of VPC, EC2, S3, DMS, and Glue; Bachelor's degree in Software Engineering, Computer Science, or Information Systems (or equivalent experience); Excellent verbal and written communication skills, including the ability to describe complex technical concepts in relatable terms; Ability to manage and prioritize multiple workstreams with confidence in making decisions about prioritization; Data-driven mentality; Self-motivated, responsible, conscientious, and detail-oriented; Effective oral and written communication skills; Ability to learn and maintain knowledge of multiple application areas; Understanding of industry best practices pertaining to Quality Assurance concepts and procedures; Bachelor's degree in Computer Science, Engineering, or relevant fields with 3+ years of experience as a Data and Solution Architect supporting Enterprise Data and Integration Applications or a similar role for large-scale enterprise solutions; 3+ years of experience in Big Data Infrastructure and tuning experience in Lakehouse Data Ecosystem, including Data Lake, Data Warehouses, and Graph DB; AWS Solutions Architect Professional Level certifications; Extensive experience in data analysis on critical enterprise systems like SAP, E1, Mainframe ERP, SFDC, Adobe Platform, and eCommerce systems