Role Overview

We are seeking an experienced Solution Architect with 10+ years of expertise in designing and delivering enterprise-scale Data, Analytics, and AI solutions. The ideal candidate will possess deep hands-on experience with Databricks and Google Cloud Platform (GCP) and be responsible for architecting modern cloud-native data platforms that enable advanced analytics, AI/ML, and business transformation initiatives.

This is a strategic and hands-on leadership role requiring strong expertise in Databricks Lakehouse Architecture, cloud data modernization, data engineering, governance, and stakeholder management.

The Solution

Architect will work closely with business stakeholders, engineering teams, and leadership to define scalable, secure, and high-performing solutions that drive measurable business outcomes. Inspired by internal Databricks Solution Architect role patterns emphasizing Lakehouse architecture, governance, cloud integration, and stakeholder leadership

Roles & Responsibilities

- Design and architect enterprise-scale Data & Analytics platforms using Databricks Lakehouse Architecture on GCP.
- Define end-to-end solution blueprints covering data ingestion, transformation, governance, security, storage, and consumption layers.
- Lead architecture discussions and convert business requirements into scalable technical solutions.
- Architect batch and real-time data pipelines using Apache Spark, Databricks, Delta Lake, and GCP services.
- Drive implementation of Medallion Architecture (Bronze, Silver, Gold) and data lifecycle management best practices.
- Design integration patterns across GCP ecosystem including BigQuery, Cloud Storage, Pub/Sub, Dataflow, Composer, and Vertex AI.
- Establish architecture standards, security frameworks, data governance, and performance optimization strategies.




- Lead cloud modernization and migration initiatives from on-premises and legacy platforms to Databricks on GCP.
- Provide technical leadership, mentoring, and architectural guidance to Data Engineers, Technical Leads, and Development teams.
- Collaborate with business, product, and delivery stakeholders to define technology roadmaps and long-term platform strategies.
- Conduct architecture reviews, design assessments, performance tuning, and cost optimization exercises.
- Support pre-sales activities including solutioning, effort estimation, technical proposals, and client presentations.
- Ensure solutions adhere to enterprise security, compliance, and regulatory requirements.
- Drive adoption of DevOps, CI/CD, Infrastructure as Code (IaC), and cloud engineering best practices.

Ideal Candidate

- 10+ years of experience in Data Engineering, Cloud Architecture, Analytics, or Enterprise Solution Architecture.
- Mandatory hands-on experience with Databricks and Google Cloud Platform (GCP).
- Strong expertise in Databricks Lakehouse, Delta Lake, Apache Spark, Unity Catalog, and data governance frameworks.
- Proven experience designing large-scale cloud-native data platforms and modernization programs.
- Deep understanding of Data Warehousing, ETL/ELT frameworks, Data Lakes, Data Modeling, and Analytics ecosystems.
- Experience with GCP services such as BigQuery, Cloud Storage, Dataflow, Pub/Sub, Composer, Vertex AI, and IAM.
- Exposure to AI/ML, MLOps, GenAI, and advanced analytics solutions is highly desirable.
- Strong knowledge of DevOps, CI/CD pipelines, Terraform, Infrastructure as Code, and cloud security best practices.
- Excellent communication, stakeholder management, consulting, and client-facing skills.
- Relevant Databricks and GCP certifications will be a solid advantage.

📌 Architect - Data & AI (Mumbai)
🏢 Exponentia.ai
📍 Mumbai