Data Engineer

SG Analytics

Chennai District

Hybrid

INR 3,000,000 - 5,400,000

Full time

7 days ago
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Job summary

SG Analytics seeks a seasoned Senior Data/Software Engineer to design and scale AI agents, ETL pipelines, and data federation for enterprise-grade applications in Chennai. The role emphasizes GenAI integration, data security, and compliant data lifecycles, with leadership in Python, PySpark, and Databricks architectures.

You will drive architecture, implement CI/CD, and collaborate across teams to deliver high-velocity automation and reliable data platforms.

Qualifications

  • 8+ years in large-scale software engineering or data platform development.
  • 5+ years of hands-on technical lead experience in Python, PySpark, and Databricks pipeline architectures.
  • Background in Banking, Financial Services, Retail Products (Cards, Mortgages, Deposits), or Wealth Management risk domains is strongly preferred.

Responsibilities

  • Design, develop, and maintain scalable, enterprise-grade AI agents and high-volume ELT/ETL pipelines using Python, PySpark, Databricks, Kafka, and FastAPI.
  • Implement and deploy GenAI agents using Google ADK and Google Flash 2.5+ LLMs to power application automation and workflow optimization via Human-in-the-Loop (HIL) design.
  • Build and maintain data federation layers for Lambda and Data Mesh architectures using Starburst to enable machine learning, deep learning, and NLP use cases.
  • Develop, deploy, and automate resilient microservice integrations supporting data-intensive applications on Kubernetes and OpenShift cloud-native platforms.
  • Integrate agentic AI tools such as Devin.AI and GitHub Copilot via Model Context Protocol (MCP) and advanced prompt engineering to maximize development velocity.
  • Enforce data quality, security, and risk compliance across the data lifecycle, ensuring adherence to regulatory standards and internal control policies.
  • Establish CI/CD pipelines, unit testing frameworks, and engineering best practices to support high-availability platform deployments.

Skills

Python
PySpark
Databricks
Kafka
FastAPI
GenAI Agents
Google ADK
LLMs
MCP
Kubernetes
OpenShift
CI/CD
Data Modeling
Data Warehousing
Data Mesh

Tools

Starburst
OpenShift
Docker
Kubernetes
GitHub Copilot
Devin.AI

Job description

Roles and Responsibilities


  • Design, develop, and maintain scalable, enterprise-grade AI agents and high-volume ELT/ETL pipelines using Python, PySpark, Databricks, Kafka, and FastAPI.

  • Implement and deploy GenAI agents using Google ADK and Google Flash 2.5+ LLMs to power application automation and workflow optimization via Human-in-the-Loop (HIL) design.

  • Build and maintain data federation layers for Lambda and Data Mesh architectures using Starburst to enable machine learning, deep learning, and NLP use cases.

  • Develop, deploy, and automate resilient microservice integrations supporting data-intensive applications on Kubernetes and OpenShift cloud-native platforms.

  • Integrate agentic AI tools such as Devin.AI and GitHub Copilot via Model Context Protocol (MCP) and advanced prompt engineering to maximize development velocity.

  • Enforce data quality, security, and risk compliance across the data lifecycle, ensuring adherence to regulatory standards and internal control policies.

  • Establish CI/CD pipelines, unit testing frameworks, and engineering best practices to support high-availability platform deployments.




Preferred Candidate Profile

Experience:



  • Overall Experience: 8+ years in large-scale software engineering or data platform development.

  • Relevant Experience: 5+ years of hands-on technical lead experience in Python, PySpark, and Databricks pipeline architectures.

  • Domain Experience: Background in Banking, Financial Services, Retail Products (Cards, Mortgages, Deposits), or Wealth Management risk domains is strongly preferred.




Technical Expertise


  • Core Data Engineering: Python, PySpark, Databricks, SQL, Kafka, Data Modeling, Data Warehousing.

  • AI & Microservices: GenAI Agents, Google ADK, LLM Integrations (Flash 2.5+), MCP, FastAPI, Microservices, Prompt Engineering.

  • Platform & Infrastructure: Data Mesh, Starburst, OpenShift, Kubernetes, Docker, CI/CD.

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