Data Modeller

6-10 Years

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Job Description

Key Responsibilities

Data Modeling & Design

Design, build, and maintain conceptual, logical, and physical data models for data warehouses, data lakes, and operational data stores.
Apply dimensional modeling techniques (Kimball star/snowflake schemas, slowly changing dimensions, conformed dimensions) and Inmon-style normalized enterprise models as appropriate.
Define naming conventions, modeling standards, and reusable design patterns; review peers models and provide constructive feedback.
Partner with data engineers to translate models into performant physical implementations and ELT/ETL pipelines.

Requirements Gathering & Stakeholder Engagement

Lead workshops with business stakeholders, product owners, and SMEs to elicit data requirements and translate them into clear modeling artifacts.
Document business definitions, source-to-target mappings, lineage, and data quality rules.
Act as a trusted advisor to analytics and engineering teams on the right modeling approach for a given use case.

Data Governance & Metadata

Curate and maintain metadata, business glossary terms, and data classifications in the enterprise governance platform (e.g., Collibra).
Support regulatory and compliance initiatives by ensuring sensitive data is properly classified, documented, and modeled.

Required Qualifications

6–10 years of professional experience in data modelling or a closely related data discipline.
Proficiency with at least one industry-standard data modeling tool (e.g., erwin Data Modeler, ER/Studio, SAP PowerDesigner, SqlDBM).
Excellent communication skills with the ability to explain complex data concepts to both technical and non-technical audiences.

Preferred Qualifications

CDVP2 (Certified Data Vault 2.0 Practitioner) or equivalent Data Vault certification.
CDMP (Certified Data Management Professional) or DAMA-DMBOK familiarity.
Experience modeling for cloud data platforms (Snowflake, Databricks, BigQuery) and lakehouse architectures.
Experience with dbt, Airflow, or similar transformation/orchestration tooling.
Exposure to industry data models (e.g., FSLDM) relevant to the organization's domain.
Familiarity with master data management (MDM), reference data, and data product / data mesh concepts.
Experience supporting regulatory frameworks such as CCPA, HIPAA, or SOX.