Databricks Cloud Platform Architect

Job Title: Databricks Cloud Platform Architect - AWS

Location: Indianapolis, IN

Duration: Long Term

Client: Direct

Role Summary

We are seeking an experienced Cloud Platform Architect to design and lead secure, scalable, enterprise-grade cloud and data-platform solutions with a strong focus on AWS and Databricks. The role combines architecture leadership, hands-on technical depth, platform modernization, governance, security, and stakeholder management across complex enterprise environments.

Key Responsibilities

• Own end-to-end cloud and platform architecture across compute, storage, networking, identity, security, data, integration, observability, and deployment layers.

• Design secure, highly available and scalable AWS architectures aligned with enterprise architecture standards, governance requirements, and operational best practices.

• Architect and guide implementation of Databricks-based Lakehouse and data-platform solutions, including workspace architecture, Unity Catalog, Delta Lake, data ingestion, transformation, and workload governance.

• Define target-state architecture, modernization strategies, migration roadmaps, reference architectures, and reusable platform patterns for enterprise workloads.

• Translate business and technical requirements into solution blueprints, architecture decisions, implementation plans, and non-functional requirements.

• Establish cloud security, identity and access management, encryption, network segmentation, compliance controls, logging, monitoring, resilience, disaster recovery, and cost-optimization practices.

• Drive Infrastructure-as-Code and automated platform provisioning using tools such as Terraform and/or AWS CloudFormation.

• Define CI/CD and DevOps patterns for infrastructure, applications, and data workloads using modern source-control and deployment practices.

• Partner with engineering, data, security, DevOps, product, and business teams to ensure architecture is implementable, supportable, and aligned with delivery objectives.

• Lead architecture reviews, technical workshops, design governance, troubleshooting, and performance optimization for complex cloud and data-platform environments.

• Provide technical leadership and mentoring to engineers and act as a trusted advisor to senior client and delivery stakeholders.

Required Experience & Skills

• 10+ years of overall technology experience, including substantial experience in cloud, platform, solution, data, or enterprise architecture roles.

• Deep hands-on architecture experience with Amazon Web Services (AWS), including core services across compute, storage, networking, IAM, security, databases, monitoring, and integration.

• Strong hands-on experience with Databricks in enterprise environments, including Lakehouse architecture, Delta Lake, Unity Catalog, workspace governance, and data engineering patterns.

• Strong understanding of modern data architecture patterns such as Lakehouse, data products, data mesh concepts, batch and streaming ingestion, and governed analytics platforms.

• Experience with Python, PySpark and SQL sufficient to review designs, validate technical approaches, and work closely with engineering teams.

• Strong experience with Infrastructure-as-Code, preferably Terraform; experience with CloudFormation is beneficial.

• Experience designing CI/CD, containerized and cloud-native deployment patterns; familiarity with Docker and Kubernetes/EKS is preferred.

• Strong knowledge of cloud security, IAM, networking, observability, high availability, disaster recovery, performance, and FinOps/cost optimization.

• Proven ability to lead architecture discussions with senior technical and business stakeholders and communicate complex concepts clearly.

Certification Requirement

• Current AWS and/or Databricks professional-level certification is required or strongly expected for consideration.

• Relevant certifications may include AWS Certified Solutions Architect - Professional, AWS Certified DevOps Engineer - Professional, Databricks Certified Data Engineer Professional, Databricks Certified Machine Learning Professional, or comparable advanced credentials.