About the role :

We are looking for a business-facing Analytics Data Modeler to act as the bridge between stakeholders and our data & engineering teams. You will own the middle layer: understanding business needs, translating them into clear technical requirements, and designing the data models and specifications that enable robust enterprise reporting and analytics.

What you will do :

1. Business & requirements :

- Work closely with business stakeholders to understand goals, KPIs, and processes.

- Lead workshops and interviews to gather and structure reporting/analytics requirements.

- Translate business needs into precise functional and technical requirements.

- Define and maintain business definitions for core entities, metrics, and KPIs.

2. Data modeling & design :

- Design logical and physical data models for the enterprise reporting layer (e.g., star schemas, dimensional models, semantic entities).

- Create and maintain source-to-target mappings and transformation specifications.

- Define data contracts and interface specifications between source systems, the warehouse, and BI layers.

- Work closely with data engineers and BI developers so that models are implemented correctly and efficiently.

3. Hands-on data work :

- Use SQL to explore and profile source data, validate assumptions, and assess data quality.

- Write SQL to prototype data transformations and models (e.g., views, CTEs, dbt models, or equivalent in your stack).

- Trace metrics and attributes end-to-end: from business definition to underlying source fields and logic.

- Support engineers and BI developers with clear specifications, test cases, and acceptance criteria.

4. Governance, quality & documentation :

- Own functional and technical documentation for your domains (definitions, models, mappings, logic).

- Help establish and enforce standards for modeling, naming, and metric definitions.

- Contribute to data quality rules and acceptance tests for critical datasets.

- Act as a subject-matter expert for what data means and how it should be modeled.

What you will bring :

Must-haves :

- Experience in a BI / analytics-oriented role (e.g., BI Analyst, Analytics Engineer, Data Modeler, Functional Analyst, or similar).

- Strong SQL skills; comfortable with complex joins, aggregations, and investigative queries.

- Practical experience designing data models for analytics and reporting (dimensional/star schema, fact/dimension concepts, slowly changing dimensions, etc.).

- Demonstrated ability to gather and refine business requirements and convert them into technical specs and models.

- Strong communication skills with the ability to talk to both business stakeholders and technical teams.

- Proactive, hands-on mindset.

Nice-to-haves :

- Experience with enterprise data warehouses and modern cloud platforms (e.g., Snowflake, BigQuery, Redshift, Azure Synapse).

- Familiarity with data modeling tools (e.g., ER/Studio, ERwin, db docs, Lucidchart, etc.).

- Understanding of ETL/ELT concepts.

- Experience in your industry and knowledge of common KPIs and data domains.

What success looks like :

- Stakeholders see their needs accurately reflected in data models and validated datasets.

- Data engineers and BI developers have clear, unambiguous specifications and models to build from.

- Core entities and metrics are consistently defined, reducing rework and misinterpretation.

- You become the go-to person for how things should be modeled and what the data really means.