03 Sep
|
AkzoNobel
|
Pune
Job Description
Dear Candidate,
n
n
Greetings from AkzoNobel (Experts in the proud craft of making paints and coatings since 1792)
n
n
We are hiring for the role of Senior Data Modeler at Pune (Hybrid role), below are additional details as required.
n
n
Skills - Design & Architecture, Azure Databricks, Data Modeling, SQL etc.
n
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
n
What youll do
n
n
- Business & requirements *
n
- Work closely with business stakeholders to understand goals, KPIs, and processes.
n
- Lead workshops and interviews to gather and structure reporting/analytics requirements.
n
- Translate business needs into precise functional and technical requirements.
n
- Define and maintain business definitions for core entities, metrics, and KPIs.
n
- Data modeling & design (no report building)*
n
- Design logical and physical data models for the enterprise reporting layer (e.g., star schemas, dimensional models, semantic entities).
n
- Create and maintain source-to-target mappings and transformation specifications.
n
- Define data contracts and interface specifications between source systems, the warehouse,
and BI layers.
n
- Work closely with data engineers and BI developers so that models are implemented correctly and efficiently.
n
- Hands-on data work (SQL & analysis)*
n
- Use SQL to explore and profile source data, validate assumptions, and assess data quality.
n
- Write SQL to prototype data transformations and models (e.g., views, CTEs, dbt models, or equivalent in your stack).
n
- Trace metrics and attributes end‑to‑end: from business definition to underlying source fields and logic.
n
- Support engineers and BI developers with transparent specifications, test cases, and acceptance criteria.
n
- Governance, quality & documentation *
n
- Own functional and technical documentation for your domains (definitions, models, mappings, logic).
n
- Help establish and enforce standards for modeling, naming, and metric definitions.
n
- Contribute to data quality rules and acceptance tests for critical datasets.
n
- Act as a subject-matter expert for what data means and how it should be modeled.”
n
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).
n
- Strong SQL skills; comfortable with complex joins, aggregations, and investigative queries.
n
- Practical experience designing data models for analytics and reporting (dimensional/star schema, fact/dimension concepts, slowly changing dimensions, etc.).
n
- Demonstrated ability to gather and refine business requirements and convert them into technical specs and models.
n
- Strong communication skills with the ability to talk to both business stakeholders and technical teams.
n
- 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).
n
- Familiarity with data modeling tools (e.g., ER/Studio, ERwin, db docs, Lucidchart, etc.).
n
- Understanding of ETL/ELT concepts and how pipelines support your models (without necessarily building the pipelines yourself).
n
- Experience in [your industry] and knowledge of common KPIs and data domains.
n
n
n
What success looks like
n
n
- Stakeholders see their needs accurately reflected in data models and validated datasets.
n
- Data engineers and BI developers have clear, unambiguous specifications and models to build from.
n
- Core entities and metrics are consistently defined, reducing rework and misinterpretation.
n
- You become the go‑to person for how things should be modeled and what the data really means.
n
n
n
Regards,
n
n
n
Team AkzoNobel
📌 Senior Data Modeler (Pune)
🏢 AkzoNobel
📍 Pune