Bus Proc And Strat Senior Analyst

NTT DATA North America; Chennai District; On-site; INR 1,000,000 - 1,700,000; Full time

Job summary

NTT DATA North America in Chennai is seeking an Associate Data & AI Engineer (G9) to design and implement data pipelines on Azure and contribute to GenAI initiatives. You will work on Databricks, PySpark, and Python to enable analytics and AI use cases.

The role combines data engineering with AI development, requiring hands-on coding, curiosity, and collaboration with senior engineers. A strong foundation in Azure and AI concepts is essential.

Qualifications

• 3–5 years of experience in data engineering, software engineering, or AI/ML roles.
• Hands-on experience with Python.
• Working knowledge of SQL and data handling.
• Exposure to Microsoft Azure (Data Factory, storage, or compute services).
• Basic experience with Azure Databricks or PySpark.
• Exposure to Generative AI concepts, such as LLMs and prompt engineering.

Responsibilities

• Support design and development of data pipelines using Azure Data Factory, Databricks, and related services.
• Develop data transformations using SQL and PySpark.
• Work with structured and unstructured data to support analytics and AI use cases.
• Contribute to Generative AI solutions using LLMs and RAG pipelines.
• Assist in prompt engineering and testing of AI applications.

Skills

Python

SQL

Data handling

ETL/ELT

LLMs

LangChain

Azure

PySpark

Tools

Azure Data Factory

Azure Databricks

PySpark

LangChain

OpenAI / Azure OpenAI

Job description

Job Description

Job Summary

We are looking for an Associate Data & AI Engineer (G9) with a solid foundation in data engineering on Azure and growing experience in Generative AI technologies such as RAG and LLM-based solutions.

This is an individual contributor role suited for a candidate who is eager to expand their expertise across data engineering and AI, working on modern data platforms and emerging AI use cases.

The ideal candidate is hands‑on, curious, and adaptable, with the ability to contribute to both data pipeline development and AI‑driven solutions.

Key Responsibilities

Data Engineering

• Support the design and development of data pipelines using Azure Data Factory, Databricks, and related services.
• Develop and maintain data transformations and workflows using SQL and PySpark.
• Work with structured and unstructured data to support analytics and AI use cases.
• Assist in implementing data models and optimizing data processing performance.

GenAI & AI Development

• Contribute to building Generative AI solutions using LLMs (e.g., Azure OpenAI, OpenAI).
• Assist in developing RAG pipelines (data ingestion, embeddings, retrieval).
• Support implementation of basic Agentic AI workflows using frameworks like LangChain or similar.
• Participate in prompt engineering and testing of AI applications.

Databricks & Processing

• Use Azure Databricks for data processing and transformation tasks.
• Develop and maintain PySpark-based pipelines under guidance from senior team members.

Python & Machine Learning

• Write Python code for data processing, automation, and basic ML workflows.
• Assist in data preparation, feature engineering, and model evaluation.

Collaboration & Learning

• Work closely with senior engineers, architects, and stakeholders on project delivery.
• Actively learn and adopt new technologies in Azure and Generative AI.
• Contribute to documentation and knowledge sharing within the team.

Required Skills & Experience

Mandatory

• 3–5 years of experience in data engineering, software engineering, or AI/ML roles.
• Hands‑on experience with Python.
• Working knowledge of SQL and data handling.
• Exposure to Microsoft Azure (Data Factory, storage, or compute services).
• Basic experience with Azure Databricks or PySpark.
• Exposure to Generative AI concepts, such as:
  • LLMs and prompt engineering
  • Basic understanding of RAG workflows
• Experience with data pipelines (ETL/ELT) concepts.

Nice to Have

• Hands‑on experience with Azure OpenAI or similar LLM APIs.
• Basic understanding of machine learning concepts and libraries.
• Experience with Power BI or data visualization tools.