Senior Data & AI Architect - Databricks, AWS & GenAI

Nagarro; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Nagarro is hiring an experienced Data & AI Architect to design scalable, secure data and AI solutions across the enterprise. The role emphasizes Databricks, AWS Bedrock, GenAI, data governance, and API-driven integrations.

Responsibilities include architecture design, data modeling, pipeline optimization, and collaboration with engineers, scientists, and stakeholders to deliver reusable data products and compliant solutions.

Qualifications

• We are seeking 8+ years in data engineering or data architecture with cloud expertise.
• Hands-on experience with Databricks and modern cloud data platforms is required.
• Strong knowledge of PySpark, SQL, data governance, and data modeling.
• Experience with AWS Bedrock and GenAI/AI-agent solutions is preferred.
• Ability to design scalable data products and enterprise data platforms.
• Experience with REST/API-based integrations and data pipeline development.

Responsibilities

• Design scalable enterprise data architectures using Databricks and AWS.
• Define patterns for ingestion, processing, storage, transformation, and serving.
• Model and optimize data warehouses and data marts across the enterprise.
• Establish governance, security, quality, and lineage frameworks.
• Develop data pipelines with PySpark, SQL, and ETL frameworks.
• Lead architecture reviews and guide cross-functional teams.

Skills

Databricks

AWS

PySpark

SQL

Enterprise Data Architecture

Data Governance

Data Modeling

Data Pipelines

API Integrations

GenAI/AI Agents

Cloud-Native Architectures

Delta Lake

Tools

AWS Bedrock

Databricks Genie

Job description

Nagarro is hiring an experienced Data & AI Architect to design scalable, secure data and AI solutions across the enterprise. The role emphasizes Databricks, AWS Bedrock, GenAI, data governance, and API-driven integrations.

Responsibilities include architecture design, data modeling, pipeline optimization, and collaboration with engineers, scientists, and stakeholders to deliver reusable data products and compliant solutions.