Data Architect
Snap · Bengaluru
- Experience7–11 yrs
- SalaryNot disclosed
- Work modeonsite
- Levelexecutive
- Posted6 Sept 2026
About Snap
Snap is hiring in Bengaluru in technology software. This role looks for around 7+ years of experience.
Skills
- enterprise data modelling
- master data management
- Databricks
- Erwin Data Modeller
- SQL
- Spark SQL
- Python
- PySpark
- data governance
- data quality
- metadata
- data lineage
- Delta Lake
- Unity Catalog
- Informatica MDM
- Informatica R360
- data architecture
- dimensional modelling
- canonical modelling
- normalised modelling
- data integration
- ELT/ETL
The role
A data architect at a technology software company designs enterprise data models and governs master data management for transactional and analytical systems, using Databricks and Erwin Data Modeller. The role applies data governance, SQL, and Python to shape canonical, dimensional, and lakehouse architectures.
Full job description
We are seeking an Enterprise Data Modeller / Data Architect to design, govern, and evolve enterprise-wide data models, master data, and reference data across a complex transactional and analytical landscape.
You will be responsible for defining canonical, transactional and dimensional enterprise data models, master and reference data structures, and for ensuring consistent, governed data consumption across operational and analytical use cases.
The candidate will have responsibilities across the following functions:
Enterprise Data Modelling:
Design and maintain conceptual, logical, and physical data models using Erwin Data Modeller, including subject area models and cross-domain canonical models.
Define and enforce enterprise data standards (naming, normalisation, domains, data types).
Maintain data dictionaries, model documentation, and change control processes.
Master Reference Data Management:
Architect and implement Master Data Management (MDM) solutions using Informatica MDM, covering Customer, Product, Supplier, Pricing, and Party domains.
Design golden record, match-merge rules, survivorship logic, and source system trust frameworks.
Define and manage reference data models (code sets, hierarchies, value lists) using Informatica R360
Establish stewardship workflows, data governance alignment, and lifecycle management for master and reference data.
Ensure consistent propagation of mastered and reference data to downstream platforms including Databricks, ERP, CRM, and OMS systems.
Data Architecture:
Databricks Lakehouse.
Define data architecture patterns for Databricks Lakehouse using Delta Lake, Unity Catalogue, and medallion (Bronze/Silver/Gold) architecture.
Translate enterprise transactional and MDM models into optimised analytical schemas and data marts.
Partner with data engineering teams to implement ELT/ETL pipelines (Spark SQL / PySpark) with data validation and reconciliation.
Transactional, Master and Reference Data systems integration.
Requirements:
10+ years of experience in enterprise data modelling and data architecture roles.
Strong hands-on experience with Erwin Data Modeller in large-scale environments is preferred.
Experience with Databricks (Delta Lake, Spark, Unity Catalogue).
Advanced SQL and strong understanding of normalised, dimensional, and canonical modelling approaches.
Experience integrating major enterprise applications (ERP, CRM, OMS, MDM, AR systems).
Strong understanding of data governance, data quality, metadata, and lineage.
Excellent communication skills across business and technical audiences.
Core Technology Stack:
Modelling: Erwin Data Modeller.
Analytics Platform: Databricks (Delta Lake, Unity Catalogue), Microsoft PowerBI.
Languages: SQL, Spark SQL, Python / PySpark.
Governance/Data Quality: Unity Catalog/Informatica DG/DQ.