DATA ARCHITECT (Multiple India Locations

DATA ARCHITECT

Experience:

613 Years

Locations:

Hyderabad / Bangalore / Chennai / Pune / Mumbai

Note: Candidate from any location any apply

Required Technical Skills

• Design, develop, and govern robust, scalable, and secure data architectures on Microsoft Azure to support analytics, AI/ML, and GenAI workloads.
• Architect and manage Azure-native data platforms including:
• Azure Data Lake Storage
• Azure Synapse Analytics
• Azure SQL
• Azure Data Factory
• Define data ingestion, transformation, and storage strategies aligned to modern cloud data patterns such as:
• Lakehouse Architecture
• Medallion Architecture

Must Have Skills

1. Strong hands-on experience in Azure Data Architecture for enterprise-scale systems.
2. Proficiency in Python and SQL for data transformation, validation, and performance optimization.
3. Extensive experience with ETL/ELT pipelines using Azure Data Factory, Synapse Pipelines, or equivalent orchestration tools.
4. Strong understanding of:

• Azure Data Lake
• Azure Synapse Analytics
• Azure SQL
• Data Warehousing Concepts

1. Experience defining and enforcing:

• Data Governance
• Data Quality
• Data Lineage
• Access Controls
• using Azure-native or integrated tools (e.g., Microsoft Purview).

Good to Have

• Experience with Vector Databases, embeddings, and data chunking strategies for Azure OpenAI / GenAI use cases.
• Familiarity with AI/ML data preparation, feature engineering, and model-ready datasets.
• Knowledge of Azure security, networking, and compliance controls applied to data platforms.

Responsibilities

1. Design and implement scalable, secure Azure-based data architectures supporting analytics, AI/ML, and GenAI initiatives.
2. Build and maintain ETL/ELT pipelines using Azure-native tools.
3. Orchestrate complex Azure data workflows ensuring reliability, availability, and performance.
4. Define and enforce data governance policies including data quality, lineage, retention, and access management.
5. Ensure security, compliance, and cost optimization of Azure data platforms.