Key Skills: Dimensional Modeling, SQL, ETL/ELT, ERP/CRM, Schema Data Modeling, Semantic Layer, Data Governance.
Proven experience in enterprise data modeling, with deep expertise in dimensional modeling (Kimball methodology).
Strong knowledge of star schema and snowflake schema design, fact and dimension tables, conformed dimensions.
Experience modeling data from ERP/CRM systems (SAP, Oracle EBS, Salesforce, Workday) - understanding of source table structures.
Proficiency in building semantic layers using modern tools (dbt, LookML, Power BI Tabular, Cube.js, AtScale).
Advanced SQL skills including complex joins, window functions, aggregations, and query optimization.
Experience defining business metrics and KPI frameworks - translating business logic into data model calculations.
Strong understanding of data modeling tools (ERD tools, data dictionaries) and documentation best practices.
Knowledge of modern data warehouses (Snowflake, Databricks, BigQuery) and their modeling capabilities.
Practical experience working alongside data engineering teams to implement models in ETL/ELT pipelines using tools such as dbt, Spark, Dataflow, or Airflow orchestrated SQL.
Experience with AI-powered data modeling tools or using AI tools like Cursor, Co-pilot, Claude to accelerate model design and documentation (Preferred).
Knowledge of Data Vault 2.0 or Anchor modeling methodologies for enterprise data warehousing (Preferred).
Experience with dbt (data build tool) for analytics engineering - models, tests, documentation, and lineage (Preferred).
Familiarity with Master Data Management (MDM) concepts - golden records, survivorship rules, hierarchy management (Preferred).
Experience with data governance frameworks - metadata management, data quality rules, lineage tracking (Preferred).
Knowledge of Python for data model automation, testing, or transformation logic (Preferred).
Qualifications:
Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field.
Job Description:
Design and implement dimensional data models (star schema, snowflake schema) following Kimball methodology for analytical applications.
Build semantic layers and metrics frameworks that abstract technical complexity and enable self-service analytics.
Model data from ERP systems (SAP, Oracle) and CRM platforms (Salesforce, Workday) into conformed dimensions and fact tables.
Define and govern key business metrics, KPIs, and calculations in collaboration with product owners and domain experts.
Create and maintain comprehensive data dictionaries, business glossaries, and data lineage documentation.
Build and maintain reusable SQL/dbt models and lightweight transformation scripts to operationalize dimensional models and metric logic as part of production data pipelines.