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 up-to-date 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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📌 Databricks Architect (Cloud, Data & AI) (Winnipeg)
🏢 KData AI
📍 Winnipeg