Description

Key Skills: Databricks, SQL, Python, Spark, LLM, LLM Ops, Azure Databricks, DevSecOps, Google Cloud Platform, CICD, Financial Services, MLOps, ETL, Generative AI, Large Language Model

Roles and Responsibilities:

• Architect and design scalable data platforms and lakehouse solutions using Azure Databricks, Spark, and Delta Lake.
• Build and standardize Databricks notebook-based development patterns, including reusable frameworks and engineering best practices.
• Drive adoption of AI-powered engineering tools, including Databricks Genie, to accelerate delivery and improve developer productivity.
• Lead technical investigations, root cause analysis, and resolution of complex data engineering and platform issues.
• Provide technical leadership and mentoring across architecture, design, and implementation for AI-enabled data engineering initiatives.

Skills Required:

• 14-18 years of relevant experience in data engineering, data architecture, analytics, or software engineering.
• Azure Databricks (Databricks on Azure) with hands-on experience designing enterprise solutions.
• Python, SQL, Spark, and Delta Lake for building and optimizing data pipelines and lakehouse workloads.
• Databricks notebooks development with strong patterns for maintainability, performance, and reliability.
• Databricks Genie usage for AI-assisted development and engineering acceleration.

Good to Have:

• Experience with cloud platforms and AI/ML workloads, including generative AI and large language models (LLMs).
• Knowledge of CI/CD, DevOps, DataOps, and MLOps practices for production-grade delivery.
• Experience with Banking and Financial Services (FSI) clients.

Education: Bachelor's Degree in Computer Science or related field; Master's Degree in Computer Science or related field

Key Skills

Education

Any Graduate