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.

Skills

ADF, Azure, Azure Data Factory, Databricks, Delta Lake, PySpark, star schema