Role Summary:

We are looking for a Data Modeler with 5 - 6 years of experience to support the design and delivery of finance data models on a cloud lakehouse platform.

You will contribute to conceptual, logical, and physical modeling, curated layer definition, and semantic views on Databricks, governed through Unity Catalog or a standard catalog.

You will work with Finance SMEs and the Technology team under the guidance of senior team members, owning well-defined modeling workstreams.

Key Responsibilities:

- Support design of conceptual and logical data models for Revenue, Expense, Sourcing, and Other Finance domains based on Stakeholder requirements.

- Define and update fact, dimension, bridge, and aggregate tables using dimensional (Kimball) modeling, including SCDs, conformed dimensions, surrogate keys, and grain definition.

- Define and refine semantic views and business metrics/KPIs (e.g., revenue, margin, spend, variance) using Databricks SQL views, metric views, or BI semantic layers.

- Collaborate with Data Engineering to translate logical models into physical tables and views, and support curated layer definition within the Medallion Architecture (Bronze/Silver/Gold).

- Organize data assets in Unity Catalog (catalog - schema - table/view) or a standard catalog; maintain descriptions, tags, and sensitivity classifications.

- Create and maintain ERDs, data dictionaries, source-to-target mappings (STTM), and model documentation, with traceability from requirements to physical models.

- Validate physical implementations against approved models and flag gaps.

- Participate in agile ceremonies, communicate progress and risks, and support junior team members through reviews and knowledge sharing.

Required Skills:

- 5 - 6 years in data modeling, data warehousing, or data engineering, with 1.5 - 2+ years on a cloud data platform, preferably Databricks.

- Strong hands-on dimensional modeling and solid understanding of conceptual, logical, and physical modeling.

- Working knowledge of Databricks (Delta Lake, Databricks SQL, Medallion Architecture) and Unity Catalog and/or Hive metastore.

- Exposure to semantic modeling (semantic views, metric definitions, BI semantic layers).

- Strong SQL skills (joins, window functions, CTEs); basic PySpark/Python is a plus.

- Familiarity with STTM, lineage, metadata management, and data quality/reconciliation practices.

- Clear communication, strong documentation habits, and the ability to work independently with moderate guidance in an agile team.

Good to have:

- Prior experience working on Finance domain data (e.g., GL, revenue, AP/AR, procurement)

- Experience with a data modeling tool such as ERwin, ER/Studio, PowerDesigner, SQLDBM, or Lucidchart

- Exposure to ERP systems

- Databricks/cloud certifications

- Experience with Power BI/Tableau

Key Deliverables:

- Conceptual and logical data models for assigned domain(s)

- Fact/dimension schemas and semantic view specifications

- Physical model and curated layer design inputs

- Data dictionaries, STTM, and model documentation