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
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.
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.
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.
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.
Requirements
Required Qualifications & Experience
Experience:
12+ years of technology experience in Enterprise Infrastructure, Data Engineering, Multi-Cloud Architecture, and AI Strategy.
Databricks Expertise:
Strong hands-on architectural experience with Databricks Lakehouse, Delta Lake, Spark, Unity Catalog, and AI/ML integrations.
Multi-Cloud Expertise:
Proven track record architecting and deploying solutions across AWS, Azure, and GCP platforms.
Legacy Modernization:
Solid background transitioning traditional database/Hadoop environments (Oracle RAC/ASM, Cloudera/Hortonworks, Netezza, HBase) into cloud-native architectures.
Domain Exposure:
Architecture experience supporting industries such as
Healthcare, Insurance & Risk, Banking & Finance, Media, Retail, or Life Sciences .
Technical Stack & Skills
Databases & Data Platforms:
Databricks, Delta Lake, Snowflake, Redshift, BigQuery, ADLS, S3, Blob Storage, Oracle (RAC/Grid), Aurora, Netezza, Postgres, MySQL, SQL Server, HBase.
Big Data & Data Integration:
Apache Spark, Hadoop Ecosystem (HDFS, Hive, YARN, Sqoop, Oozie, Pig, Atlas, Ranger), Kafka, Azure Data Factory, AWS Glue, NiFi, Denodo (Data Virtualization), Informatica (IICS/PowerCenter), Syncsort.
AI & Advanced Analytics:
Generative AI pipeline design, Dataiku, AtScale, PowerBI.
Observability, Operations & Tools:
Grafana, SumoLogic, Git/GitStash, Jira, Bamboo, DB Visualizer.
Languages & Scripting:
Python, SQL, PL/SQL, Unix Shell Scripting, Perl Scripting.
DevOps & Infrastructure:
Terraform, AWS CloudFormation (CFT), CodeDeploy, CI/CD pipelines, Linux (RedHat), Windows AD.
Education
Master’s or Bachelor’s degree in Business Administration, Computer Science, Software Engineering, or a related technical discipline.
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