Resident Solution Architect – Databricks | 10+ Yrs | Bangalore

Resident Solution Architect – Databricks
Location: Bangalore | Function: Data & AI Consulting | Experience: 10+ Years | Level: Solution Architect / Senior Solution Architect

Are you the architect enterprise clients call when their data platform needs to scale? We're looking for a hands-on Databricks expert to design, lead and deliver enterprise-scale Data & AI solutions on the Lakehouse Platform, working as a trusted advisor to business and technology leaders.

Solution Architecture & Design

• Design and lead enterprise-scale Data & AI solutions on the Databricks Lakehouse Platform.
• Architect scalable, secure and high-performance data platforms across AWS, Azure and/or GCP.
• Define end-to-end solution architecture aligned with business and technical objectives.
• Recommend best practices for data engineering, governance, security and platform modernization.

Enterprise Delivery & Implementation

• Lead end-to-end delivery of enterprise Databricks implementations, from discovery through production deployment.
• Deliver large-scale production workloads with a focus on scalability, reliability and performance.
• Solve complex production challenges in distributed data processing, platform optimization and cloud-native architectures.
• Deliver within agreed timelines, quality standards and customer expectations.

Data Engineering & Platform Excellence

• Develop and optimize enterprise data pipelines using Apache Spark and Databricks.
• Build scalable ETL/ELT frameworks using Delta Lake and modern data engineering practices.
• Apply deep understanding of Spark architecture, execution plans and runtime optimization.
• Drive platform performance tuning, cost optimization and workload scalability.

Cloud & Modern Data Platform

• Design and implement cloud-native data solutions across AWS, Azure and GCP.
• Collaborate with platform engineering teams on CI/CD pipelines and deployment automation.
• Apply Infrastructure-as-Code and DevOps best practices.
• Support enterprise MLOps implementation and integration with modern AI workflows.

Customer Engagement & Consulting

• Lead architecture workshops, technical discovery sessions and executive presentations.
• Partner with customers to translate business challenges into scalable technical solutions.
• Provide technical leadership through implementation and post-production support.
• Build trusted-advisor relationships with business and technology stakeholders.
• Define enterprise architecture standards, reusable accelerators, coding standards and governance frameworks.
• Ensure security, compliance, data quality and operational excellence across implementations.
• Mentor engineering teams and contribute to capability building across the organization.

Requirements

Knowledge & Experience

• 10+ years of consulting and technology experience.
• Minimum 7+ years in Data Engineering, Data Platforms or Analytics.
• Minimum 6–8 enterprise Databricks implementations delivered in production environments.
• Hands-on enterprise delivery experience is mandatory.
• Experience designing and deploying large-scale distributed data platforms.
• Strong customer-facing consulting and solution architecture experience.
• Experience with global enterprise customers across multiple industries.

Education & Certifications

• Bachelor's degree in Computer Science, Engineering, IT or a related discipline (Master's preferred).
• Databricks Data Engineer Professional Certification – Mandatory.
• Additional cloud certifications (AWS, Azure or GCP) are highly desirable.

Soft Skills

• Excellent technical competency, communication and presentation skills.
• Consulting mindset with strong problem-solving ability.
• Executive presence and stakeholder management capability.
• Customer engagement and workshop facilitation skills.
• Ability to influence technical and business decision-makers.

Benefits

• Lead high-impact, enterprise-scale Databricks Lakehouse programmes.
• Work hands-on with the latest Databricks capabilities: Unity Catalog, Delta Lake, MLOps and GenAI workloads.
• High-visibility, client-facing role as a trusted advisor to senior leadership.
• Fast-track growth in one of the most in-demand specialisations in Data & AI.