Senior Databricks AI Architect

Key Responsibilities :

- Architect and design scalable data platforms and solutions using Databricks.

- Drive the adoption of AI-powered engineering tools such as Databricks Genie, Cursor, GitHub Copilot, and similar technologies to improve delivery efficiency.

- Lead technical investigations, root cause analysis, and resolution of complex data engineering and platform issues.

- Define architecture standards, best practices, and reusable frameworks for Databricks and AI-enabled engineering.

- Identify opportunities to modernize traditional engineering practices through AI-driven automation and intelligent workflows.

- Provide technical leadership and mentoring to engineering teams across architecture, design, and implementation.

- Collaborate with business stakeholders, solution architects, and delivery teams to define scalable, secure, and high-performing solutions.

- Evaluate emerging AI technologies and recommend their adoption to enhance engineering productivity and innovation.

Required Skills & Experience :

- 1015 years of experience in Data Engineering, Data Architecture, Analytics, or Software Engineering.

- Minimum 5 years of hands-on experience with Databricks (Mandatory).

- Strong expertise in designing and implementing enterprise-scale data platforms on Databricks.

- Hands-on experience with AI-powered engineering tools such as Databricks Genie, Cursor, GitHub Copilot, or similar AI platforms.

- Strong proficiency in Python, SQL, Spark, Delta Lake, and Databricks notebooks.

- Experience designing modern data architectures, ETL/ELT pipelines, and Lakehouse solutions.

- Strong analytical, problem-solving, and innovation skills with an AI-first mindset.

- Experience leading technical teams, providing architectural guidance, and driving engineering best practices.

- Excellent communication, stakeholder management, and collaboration skills.

Preferred Skills :

- Experience with Azure Databricks and cloud platforms (Azure preferred).

- Experience with AI/ML workloads, Generative AI, and Large Language Models (LLMs).

- Knowledge of CI/CD, DevOps, DataOps, and MLOps practices.

- Experience working with Banking and Financial Services (FSI) clients is highly desirable.

(ref:hirist.tech)