Senior Data Modeler

Dear Candidate,

Greetings from AkzoNobel (Experts in the proud craft of making paints and coatings since 1792)

We are hiring for the role of Senior Data Modeler at Pune (Hybrid role), below are additional details as required.

Skills - Design & Architecture, Azure Databricks, Data Modeling, SQL etc.

About the role

Were looking for a business-facing Analytics Data Modeler to act as the bridge between stakeholders and our data & engineering teams. Youll 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.

This is a hybrid between a data modeler and an analyst: hands-on with SQL and data profiling, but also leading conversations with the business to shape what we build.

What youll do

• 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.
• Data modeling & design (no report building)*
• 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.
• Hands-on data work (SQL & analysis)*
• 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 endtoend: from business definition to underlying source fields and logic.
• Support engineers and BI developers with clear specifications, test cases, and acceptance criteria.
• 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’ll 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; you take ownership, ask questions, and drive clarity rather than waiting for perfect input.

Nice-to-haves (adapt to your environment):

• 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 and how pipelines support your models (without necessarily building the pipelines yourself).
• 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 goto person for how things should be modeled and what the data really means.

Regards,

Team AkzoNobel