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Databricks Platform Architect -AWS (Onsite)

GSK Solutions Inc.Dallas, TX🇺🇸United StatesPosted 8 Sept 2026

Why This Role Stands Out

You can significantly advance your career by architecting and managing a cutting-edge Databricks Lakehouse Platform on AWS, a role perfect for a skilled Databricks and AWS professional seeking impactful work. This position offers a fantastic opportunity to shape critical data infrastructure within a reputable organization, so we encourage you to apply.

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Dallas, TX, United States
Posted
Yesterday
AWSEncryptionMLflowAirflowComplianceDatabricksJenkinsKafkaKubernetesTerraformUnity

Job Description

Job Title

Databricks Platform Architect – AWS (Onsite)

Location

Dallas, TX

Duration

6.7 Months

Interview Type

Virtual / In-Person

Note

  • This is onsite position from Toyota Plano office , expected to be in office minimum 3 days a week

  • Locals Only

Description

  • Architect and manage a secure, scalable, and highly available Databricks Lakehouse Platform on AWS.

  • Design data platforms leveraging AWS S3, Delta Lake, Unity Catalog, and Databricks Workspaces for enterprise analytics and AI.

  • Define networking architecture including VPC, PrivateLink, IAM roles, security groups, and encryption standards.

  • Establish multi-environment strategies (Dev, Test, UAT, Prod) with automated provisioning through Terraform and Infrastructure as Code (IaC).

  • Implement enterprise-wide data governance, lineage, metadata management, and compliance controls using Unity Catalog.

  • Design high-performance data ingestion and processing architectures supporting batch, streaming, and real-time analytics workloads.

  • Enable AI and GenAI capabilities through Mosaic AI, Vector Search, Model Serving, AI/BI Dashboards, and Genie Spaces.

  • Define CI/CD, monitoring, logging, and observability frameworks using GitHub, Jenkins, CloudWatch, and Databricks Workflows.

  • Optimize platform performance, reliability, scalability, and cloud costs through FinOps and workload optimization practices.

  • Provide architectural leadership and best practices for Lakehouse modernization, advanced analytics, AI governance, and enterprise data platform adoption.

  • Core Technologies: Databricks, AWS S3, Delta Lake, Unity Catalog, Spark/PySpark, Terraform, GitHub, CI/CD, CloudWatch, Mosaic AI, Genie, Vector Search, MLflow, Kafka, Airflow, Kubernetes.

 

Certification :

  • DataBricks Platform Administrator /Databricks Certified Data Engineer/

  • AWS Certification (DevOps/Solution Architect)

  • Terraform 

 

Deliverables:

-Process Flows

-Mentor and Knowledge transfer to client project team members

-Participate as primary, co and/or contributing author on any and all project deliverables associated with their assigned areas of responsibility

-Participate in data conversion and data maintenance

-Provide best practice and industry specific solutions

-Advise on and provide alternative (out of the box) solutions

-Provide thought leadership as well as hands on technical configuration/development as needed.

-Participate as a team member of the functional team

-Perform other duties as assigned. 

Top Skills

S.No

Skill Name

Experience 

1

Databricks on AWS Platform Engineer – Platform Architecture

 

2

Architect and manage a secure, scalable, and highly available Databricks Lakehouse Platform on AWS.

 

3

Design data platforms leveraging AWS S3, Delta Lake, Unity Catalog, and Databricks Workspaces for enterprise analytics and AI.

 

4

Define networking architecture including VPC, PrivateLink, IAM roles, security groups, and encryption standards.

 

5

Establish multi-environment strategies (Dev, Test, UAT, Prod) with automated provisioning through Terraform and Infrastructure as Code (IaC).

 

6

Implement enterprise-wide data governance, lineage, metadata management, and compliance controls using Unity Catalog.

 

7

Design high-performance data ingestion and processing architectures supporting batch, streaming, and real-time analytics workloads.

 

8

Enable AI and GenAI capabilities through Mosaic AI, Vector Search, Model Serving, AI/BI Dashboards, and Genie Spaces.

 

9

Define CI/CD, monitoring, logging, and observability frameworks using GitHub, Jenkins, CloudWatch, and Databricks Workflows.

 

10

Optimize platform performance, reliability, scalability, and cloud costs through FinOps and workload optimization practices.

 

11

Provide architectural leadership and best practices for Lakehouse modernization, advanced analytics, AI governance, and enterprise data platform adoption.

 

Recruiter

Contact: Lokesh - - Eight three two - Nine nine zero - Two four two six

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