Description

You will architect and design scalable data platforms and lakehouse solutions using Azure Databricks, Spark, and Delta Lake.

This role is on-site.

Responsibilities

• 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.
• Design enterprise solutions using Azure Databricks with a focus on maintainability, performance, and reliability.

Required Skills

• 12+ years of relevant experience in data engineering, data architecture, analytics, or software engineering.
• Hands-on experience with Azure Databricks (Databricks on Azure) for designing enterprise solutions.
• Proficiency in Python, SQL, Spark, and Delta Lake for building and optimizing data pipelines and lakehouse workloads.
• Strong expertise in Databricks notebooks development with established patterns for code quality and performance.
• Experience with Databricks Genie for AI-assisted development and engineering acceleration.
• Knowledge of CI/CD, DevOps, DataOps, and MLOps practices for production-grade delivery.

Preferred Skills

• Experience with cloud platforms and AI/ML workloads, including generative AI and large language models (LLMs).
• Experience with Banking and Financial Services (FSI) clients.

Key Skills

Education

Any Graduate