Data Architect

Responsibilities:
Design, build, and own enterprise-scale data platforms on Azure.
Take end-to-end accountability for architecture, data pipelines, transformation frameworks, and production readiness.
Act as a bridge between business stakeholders, data engineering, and analytics teams to deliver scalable, high-performance solutions.
Design and implement data pipelines using Azure Data Factory (ADF), including REST API and external source integration.
Build data transformation workflows using Databricks (PySpark) for complex and nested JSON datasets.
Architect and implement Delta Lake-based platforms with fact and dimension models (star schema).
Define and enforce best practices for data modeling, performance optimization, and cost efficiency.
Own the full data platform lifecycle: architecture, deployment, monitoring, and support.
Establish production-readiness frameworks, including logging, alerting, and data quality checks.
Collaborate with business and analytics teams to translate requirements into scalable solutions.
Mentor engineering teams and drive architectural governance.
Requirements:
Experience building pipelines using Azure Data Factory.
Experience integrating REST APIs using Azure Data Factory.
Experience building transformations using Databricks (PySpark).
Experience handling complex and nested JSON datasets using PySpark.
Experience designing dimensional models (star schema).
Experience implementing fact and dimension tables in Databricks Delta Lake.
15-18 years of experience in enterprise data platforms, with at least 5 years in Azure data services.
Ability to bridge business, data engineering, and analytics teams.
Experience owning end-to-end production readiness, including architecture, deployment, monitoring, and support.

Experience
12-16 yrs