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 up-to-date 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.

📌 Databricks Architect (Cloud, Data & AI) (Brampton)
🏢 KData AI
📍 Brampton