Senior Engineer-Azure+AI

Cummins; Pune District; Hybrid; INR 4,000,000 - 8,000,000; Full time

Job summary

Cummins is seeking a Data Scientist with 7-10+ years of experience to design, build, and operationalize AI and analytics solutions on the Databricks Lakehouse Platform in a hybrid data and SCM planning-focused role.

The ideal candidate will implement GenAI, RAG, and agentic AI workflows, develop scalable data pipelines and dashboards, and collaborate with stakeholders to drive governance, security, and cost optimization across cloud-native architectures.

Qualifications

• 5+ years of experience designing and delivering enterprise data, analytics, AI, or engineering solutions.
• Proven experience with the Databricks Lakehouse Platform, including Unity Catalog, Delta Lake, Databricks SQL, AI/BI Dashboards, Databricks Apps, Lakebase, Workflows, and MLflow.
• Hands-on experience building production-grade GenAI, RAG, multimodal AI, agentic workflows, Vector Search, and MLOps solutions using Databricks, Azure OpenAI, AWS, Azure, or GCP.
• Strong proficiency in PySpark, SQL, Python, data engineering, machine learning, and cloud-native architectures.
• Experience with enterprise application integration, Agile delivery, and the full software development lifecycle.
• Excellent stakeholder management, problem-solving, and communication skills.

Responsibilities

• Design, build, and support enterprise data, analytics, AI, and machine learning solutions using the Databricks Lakehouse Platform
• Design and Develop scalable data pipelines, AI/BI dashboards, Databricks Apps, Lakebase applications, and data products to meet business and analytical requirements.
• Collaborate with business stakeholders, architects, and product teams to define functional and technical solution requirements.
• Design enterprise data architectures, integrations, and workflows that align with governance, security, and performance standards.
• Develop and operationalize machine learning, Generative AI, RAG, and agentic AI solutions using Databricks AI capabilities.
• Deliver trusted analytics and insights through governed data products, dashboards, and self-service analytics.
• Evaluate existing application ecosystems (including Oracle S&OP) and recommend modernization opportunities using Databricks.
• Lead solution design, implementation, testing, support, and continuous improvement while ensuring best practices for scalability, reliability, and cost optimization

Skills

Databricks Lakehouse Platform

Unity Catalog

Delta Lake

Databricks SQL

AI/BI Dashboards

Databricks Apps

Lakebase

Workflows

MLflow

GenAI

RAG

Vector Search

PySpark

SQL

Python

Cloud (Azure/AWS/GCP)

Tools

Azure OpenAI

AWS

GCP

Job description

7-10+ years

(Team is working on - Azure Data lake on data bricks platform)

Data scientist role creating value using AI (hybrid of DS and DE, with SCM planning as a functional – highly preferred)

Technically – proven exp databricks app, and lakebase (OLTP in the platform – used for maintaining information) application.

Exp with AI solution using Genie Code and Genie Space.

Key Responsibilities:

• Design, build, and support enterprise data, analytics, AI, and machine learning solutions using the Databricks Lakehouse Platform
• Design and Develop scalable data pipelines, AI/BI dashboards, Databricks Apps, Lake base applications, and data products to meet business and analytical requirements.
• Collaborate with business stakeholders, architects, and product teams to define functional and technical solution requirements.
• Design enterprise data architectures, integrations, and workflows that align with governance, security, and performance standards.
• Develop and operationalize machine learning, Generative AI, RAG, and agentic AI solutions using Databricks AI capabilities.
• Deliver trusted analytics and insights through governed data products, dashboards, and self-service analytics.
• Evaluate existing application ecosystems (including Oracle Supply Chain Planning and S&OP) and recommend modernization opportunities using Databricks.
• Lead solution design, implementation, testing, support, and continuous improvement while ensuring best practices for scalability, reliability, and cost optimization

*Qualifications and Competencies

Experience:

• 5+ years of experience designing and delivering enterprise data, analytics, AI, or engineering solutions.
• Proven experience with the Databricks Lakehouse Platform, including Unity Catalog, Delta Lake, Databricks SQL, AI/BI Dashboards, Databricks Apps, Lakebase, Workflows, and MLflow.
• Hands-on experience building production-grade GenAI, RAG, multimodal AI, agentic workflows, Vector Search, and MLOps solutions using Databricks, Azure OpenAI, AWS, Azure, or GCP.
• Strong proficiency in PySpark, SQL, Python, data engineering, machine learning, and cloud-native architectures.
• Experience with enterprise application integration, Agile delivery, and the full software development lifecycle.
• Excellent stakeholder management, problem-solving, and communication skills.