Role Overview
We are seeking a Databricks Architect to lead the vision, design, and execution of large-scale, enterprise-grade Databricks Lakehouse architectures across multi-cloud and hybrid environments. In this role, you will advise executive leadership (CIOs/CTOs), drive pre-sales and technical solution design, and lead hands-on architecture for modern data and GenAI platforms.
The ideal candidate brings 12+ years of technology experience, combining deep technical expertise in Databricks, multi-cloud strategy (AWS, Azure, GCP), TOGAF governance, data virtualization, and hands-on experience guiding enterprise modernization initiatives.
Key Responsibilities
1. Enterprise Solution Architecture & Design
- Lead architectural design and hands-on technical oversight for Databricks Lakehouse, Delta Lake, streaming pipelines, and AI-ready platforms.
- Define enterprise infrastructure reference architectures spanning cloud networking, compute, storage, security, observability, platform resiliency, disaster recovery, and compliance.
- Build end-to-end multi-cloud data integration layers and dynamic pipelines connecting legacy systems, cloud data lakes, and modern AI/ML frameworks.
- Establish governance models, architecture guiding principles, and standard frameworks (e.g., TOGAF) for enterprise platforms.
- Drive data virtualization and semantic layer strategies to streamline business intelligence and self-service analytics.
2. Client Engagement & Pre-Sales Leadership
- Serve as a trusted advisor to C-suite executives and CIOs on cloud modernization, data platform resiliency, cost optimization, and AI-enabled operational transformations.
- Partner with Sales and Account teams on pre-sales activities, RFP responses, solution design, and high-value deal shaping.
- Conduct discovery workshops, present technical blueprints (SAD, DDD), and defend technical solutions to enterprise clients.
3. AI & Data Engineering Modernization
- Architect solutions incorporating Generative AI, automated document parsing/reformatting pipelines, advanced analytics, and machine learning models within the Databricks ecosystem.
- Oversee migrations from legacy databases/Big Data infrastructure (Hadoop, Oracle, Cloudera, Netezza) to modern cloud-native Lakehouses (AWS, Azure, GCP) using structured acceleration frameworks (e.g., AWS MAP).
- Establish robust security controls, encryption protocols, enterprise authentication mechanisms (Unity Catalog, Kerberos), and performance tuning for high-throughput environments.