Dear Candidate, /n Greetings from AkzoNobel (Experts in the proud craft of making paints and coatings since 1792) /n We are hiring for the role of Senior Data Modeler at Pune (Hybrid role), below are additional details as required. /n Skills - Design & Architecture, Azure Databricks, Data Modeling, SQL etc. /n About the role /n 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. /n 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. /n What youll do /n /n

- Business & requirements*

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

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

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- Translate business needs into precise functional and technical requirements.

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

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- Data modeling & design (no report building)

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

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

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

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

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- Hands-on data work (SQL & analysis)

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

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

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

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

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- Governance, quality & documentation*

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

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

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

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

/n /n What you'll bring /n Must-haves: /n /n

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

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- Strong SQL skills; comfortable with complex joins,



aggregations, and investigative queries.

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

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

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

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- Proactive, hands-on mindset; you take ownership, ask questions, and drive clarity rather than waiting for perfect input.

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

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

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

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- Understanding of ETL/ELT concepts and how pipelines support your models (without necessarily building the pipelines yourself).

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

/n /n What success looks like /n /n

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

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

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

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

/n /n Regards, /n Team AkzoNobel

📌 Senior Data Modeler (Pune)
🏢 AkzoNobel
📍 Pune