Location: Pune
Work Mode: 5 days of work from the office.
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Role Context:
Own conceptual/logical/physical modelling for key domains, ensuring semantics, integrity, and performance. Enables consistent ETL implementation and supports analytics and ML-friendly structures.
Key Responsibilities:
- Create and maintain conceptual, logical, and physical data models.
- Define canonical structures, keys, grain, relationships, reference/master data conventions.
- Ensure time semantics are explicitly modelled (event_time vs process_time, snapshot dates).
- Provide model-driven guidance to ETL teams and validate transformation logic alignment.
- Maintain data dictionary, naming standards, domain glossary, and change impact analysis.
- Ensure models support analytics reporting and ML feature derivation (events, snapshots, aggregates).
Must Have
- 812 years in data modelling / data architecture with strong delivery alignment.
- Expertise in 3NF and dimensional modelling; canonical modelling experience preferred.
- Strong SQL profiling and validation capability.
- Cloud warehouse modelling experience (Snowflake/BigQuery/Redshift/Synapse).
- Strong understanding of SCD, temporal modelling, surrogate keys, and conformed dimensions.
- Non-technical: stakeholder communication, documentation quality, conflict resolution on definitions.
Good To Have
- Exposure to Data Vault 2.0 modelling.
- Experience modelling customer/marketing/event-driven domains.
- Familiarity with feature-store-friendly modelling patterns.
