Job Title : Databricks Architect

Job Location : Pan India

Notice Period : Any

Experience : 12-20 Years

Education : Any Bachelors Degree

About ARA's Client Global Professional Services Leader :

ARA's Client is a global professional services company with leading capabilities in digital, cloud, and security. They combine unmatched experience and specialized skills across more than 40 industries, offering Strategy and Consulting, Interactive, Technology, and Operations services. Their culture embraces the power of change to create value and shared success for clients, people, shareholders, partners, and communities.

Role Summary :

ARA's Client is seeking a highly experienced Databricks Architect to lead the design and implementation of optimized lakehouse and AI infrastructure for large-scale machine learning systems. This pivotal role involves owning end-to-end architecture, ensuring scalability, cost-efficiency, and adherence to security and compliance standards, while mentoring engineering teams.

Key Responsibilities :

- Own end-to-end architecture and design of optimized Databricks AI/ML infrastructure, including workspace, cluster, and model-serving environments.

- Design and tune scalable Databricks clusters, jobs, and pipelines using Databricks Workflows, MLflow, Unity Catalog, and Delta Lake.

- Serve as an authoritative AI infrastructure expert, applying deep knowledge of lakehouse architecture, ML lifecycle services, governance, security, and cost optimization.

- Develop and evaluate architecture alternatives, weighing trade-offs across compute, networking, storage, orchestration, and security.

- Lead architecture assessments, identifying gaps, risks, and optimization opportunities in existing and proposed environments.

- Drive architecture decision-making by documenting rationale, trade-offs, and dependencies, ensuring alignment with business SLAs.

- Define and maintain AI infrastructure roadmap inputs, capacity planning models, scaling strategies, and cost forecasts.

- Design deployment, automation, and CI/CD strategies for reliable, repeatable releases of AI systems and data pipelines.

- Establish AI monitoring and observability practices across InfraOps and MLOps, including SLAs, alerting, and performance/cost tracking.

- Integrate AI/ML systems into enterprise environments, ensuring interoperability, security, and compliance.

- Collaborate with clients, stakeholders, and engineering teams to translate requirements into actionable architecture standards.

- Set technical direction, mentor engineers, review designs/code, and promote engineering best practices.

Must-Have Qualifications :

- 12-20 years of overall experience, with significant experience in AI/ML infrastructure architecture and large-scale engineering solutions.

- Proven expertise with Databricks workspaces, clusters, Workflows, MLflow, Model Registry, Unity Catalog, Delta Lake, and Feature Engineering.

- Strong proficiency in Python, SQL, and Spark, with experience in programming/scripting languages like Java, C++, Bash, or PowerShell.

- Experience architecting scalable data and ML pipelines, distributed processing/training workloads, and high-throughput data access.

- Deep understanding of AI/ML concepts and the computing infrastructure required for production AI workloads on hyperscalers (Azure, AWS, GCP).

- Strong working knowledge of Terraform/Databricks Asset Bundles, Git-based CI/CD, DataOps, MLOps, observability, and incident response practices.

- Bachelor's degree in Computer Science, Computer Engineering, IT, or a related engineering field.

- Excellent communication, collaboration, and stakeholder alignment skills.