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Description
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Architect and manage a secure, scalable, and highly available Databricks Lakehouse Platform on AWS.
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Design data platforms leveraging AWS S3, Delta Lake, Unity Catalog, and Databricks Workspaces for enterprise analytics and AI.
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Define networking architecture including VPC, PrivateLink, IAM roles, security groups, and encryption standards.
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Establish multi-environment strategies (Dev, Test, UAT, Prod) with automated provisioning through Terraform and Infrastructure as Code (IaC).
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Implement enterprise-wide data governance, lineage, metadata management, and compliance controls using Unity Catalog.
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Design high-performance data ingestion and processing architectures supporting batch, streaming, and real-time analytics workloads.
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Enable AI and GenAI capabilities through Mosaic AI, Vector Search, Model Serving, AI/BI Dashboards, and Genie Spaces.
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Define CI/CD, monitoring, logging, and observability frameworks using GitHub, Jenkins, CloudWatch, and Databricks Workflows.
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Optimize platform performance, reliability, scalability, and cloud costs through FinOps and workload optimization practices.
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Provide architectural leadership and best practices for Lakehouse modernization, advanced analytics, AI governance, and enterprise data platform adoption.
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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 :
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.
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Top Skills
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S.No
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Skill Name
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Experience
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1
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Databricks on AWS Platform Engineer – Platform Architecture
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|
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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.
|
|
|
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