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Resident Solution Architect (RSA) - Databricks

Aptino

Remote • Today

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Contract, Third Party

Depends on Experience

Job Details

Skills

Distributed Computing
Continuous Integration
Curriculum
Data Engineering
Cloud Computing
Communication
Continuous Delivery
Operational Excellence
Optimization
Performance Tuning
Machine Learning Operations (ML Ops)
Mentorship
Google Cloud Platform
IT Management
Machine Learning (ML)
Data Governance
Good Clinical Practice
Microsoft Azure
Amazon Web Services
Roadmaps
Scalability
Analytics
Apache Spark
Databricks
DevOps
RSA
Stakeholder Management
Technical Direction
Testing
Training
Resident Solutions Architect
Data Platforms
Data Analytics
Spark Architecture
Spark Runtime Internals
Cost Optimization
AWS
Azure
GCP
Cloud Architecture
Cloud-Native Technologies
CI/CD
MLOps
Machine Learning Lifecycle
Model Deployment
Data Platform Development
Production Deployment
Databricks Development
Databricks Data Engineering Professional Certification
Data Security
Reliability
Technical Architecture
Architecture Standards
Technical Roadmaps
Enterprise Data Platforms
Data Engineering Solutions
Analytics Solutions
Cloud Optimization
Platform Optimization
Technical Leadership
Consulting
Mentoring
Troubleshooting
Best Practices
Databricks Platform Capabilities
Distributed Data Processing
Data Pipelines
Cloud Data Engineering
Enterprise Architecture
Production Support
ySpark
Python
SQL
Delta Lake
Unity Catalog
Lakehouse Architecture
ETL/ELT
Spark Optimization
Databricks Workflows
MLflow
Terraform
Git
Data Quality
Google Cloud
Delta Live Tables (DLT)
Databricks SQL
Medallion Architecture
PySpark
Infrastructure as Code (IaC)
Azure Data Factory
AWS S3
Azure Data Lake Storage (ADLS)
Kafka
Data Streaming
Workflow Orchestration
Job Clusters
Serverless Compute
Cluster Optimization
Partitioning
Caching
Query Optimization
Data Modeling
Data Warehousing
Data Lake
Data Lakehouse
Data Lineage
Data Observability
Security & Access Control
RBAC
CI/CD Automation
GitHub
Azure DevOps
Jenkins
Model Monitoring
Model Lifecycle Management
Cloud Migration
Platform Modernization
Solution Architecture
Technical Roadmap
Architecture Governance
Cost Management
FinOps

Distributed Computing
Continuous Integration
Curriculum
Data Engineering
Cloud Computing
Communication
Continuous Delivery
Operational Excellence
Optimization
Performance Tuning
Machine Learning Operations (ML Ops)
Mentorship
Google Cloud Platform
IT Management
Machine Learning (ML)
Data Governance
Good Clinical Practice
Microsoft Azure
Amazon Web Services
Roadmaps
Scalability
Analytics
Apache Spark
Databricks
DevOps
RSA
Stakeholder Management
Technical Direction
Testing
Training
Resident Solutions Architect
Data Platforms
Data Analytics
Spark Architecture
Spark Runtime Internals
Cost Optimization
AWS
Azure
GCP
Cloud Architecture
Cloud-Native Technologies
CI/CD
MLOps
Machine Learning Lifecycle
Model Deployment
Data Platform Development
Production Deployment
Databricks Development
Databricks Data Engineering Professional Certification
Data Security
Reliability
Technical Architecture
Architecture Standards
Technical Roadmaps
Enterprise Data Platforms
Data Engineering Solutions
Analytics Solutions
Cloud Optimization
Platform Optimization
Technical Leadership
Consulting
Mentoring
Troubleshooting
Best Practices
Databricks Platform Capabilities
Distributed Data Processing
Data Pipelines
Cloud Data Engineering
Enterprise Architecture
Production Support
ySpark
Python
SQL
Delta Lake
Unity Catalog
Lakehouse Architecture
ETL/ELT
Spark Optimization
Databricks Workflows
MLflow
Terraform
Git
Data Quality
Google Cloud
Delta Live Tables (DLT)
Databricks SQL
Medallion Architecture
PySpark
Infrastructure as Code (IaC)
Azure Data Factory
AWS S3
Azure Data Lake Storage (ADLS)
Kafka
Data Streaming
Workflow Orchestration
Job Clusters
Serverless Compute
Cluster Optimization
Partitioning
Caching
Query Optimization
Data Modeling
Data Warehousing
Data Lake
Data Lakehouse
Data Lineage
Data Observability
Security & Access Control
RBAC
CI/CD Automation
GitHub
Azure DevOps
Jenkins
Model Monitoring
Model Lifecycle Management
Cloud Migration
Platform Modernization
Solution Architecture
Technical Roadmap
Architecture Governance
Cost Management
FinOps

Summary

Role: Resident Solutions Architect (RSA) – Databricks

Location: Remote – US
Duration: 12 Months

Role Overview:

We are seeking an experienced Resident Solutions Architect – Databricks to provide technical leadership for enterprise-scale data engineering and analytics initiatives. The ideal candidate will work closely with client stakeholders and engineering teams to architect, implement, optimize, and scale modern data platforms using Databricks and cloud technologies.

Key Responsibilities:

Architect and deliver scalable data engineering, analytics, and data platform solutions using Databricks.
Work directly with business, client, and technical stakeholders to establish architecture standards, technical strategies, best practices, and implementation roadmaps.
Provide hands-on technical direction throughout data platform development, integration, optimization, testing, and production deployment.
Identify opportunities to improve platform performance, scalability, reliability, and cloud/Databricks cost efficiency.
Guide engineering teams in implementing CI/CD, DevOps, automation, and MLOps practices for enterprise data solutions.
Provide technical mentorship on Apache Spark, distributed processing, Spark architecture, and performance optimization.
Assess new Databricks capabilities and cloud-native technologies and recommend solutions that support business and technical objectives.
Partner with delivery teams to troubleshoot complex platform and production issues and provide architectural solutions.
Establish scalable approaches for data governance, security, reliability, and operational excellence across Databricks environments.

Required Qualifications:

7+ years of professional experience in data engineering, enterprise data platforms, analytics, or related areas.
Databricks Data Engineering Professional certification along with completion of the required Databricks training curriculum.
Demonstrated delivery of 6–8+ successful data projects, with substantial hands-on experience developing solutions within Databricks.
Strong expertise in Apache Spark and distributed computing, including Spark runtime architecture, troubleshooting, and performance tuning.
Proven ability to design and deploy modern data platforms across AWS, Azure, or Google Cloud Platform, with practical working knowledge of at least one additional cloud platform.
Experience with CI/CD pipelines, DevOps practices, automated deployments, and production-grade cloud development.
Working knowledge of MLOps, machine learning lifecycle processes, model deployment, and operationalization of ML solutions.
Strong understanding of current Databricks platform capabilities, architecture patterns, scalability, reliability, governance, and enterprise best practices.
Excellent communication and stakeholder-management skills, with the ability to operate as a trusted technical advisor for enterprise clients.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 90999382
Position Id: 9075764
Posted 8 hours ago

Fitment

Dice Job Match Score™

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Contact the job poster

Anchal Khapekar

Recruiter @ Aptino

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Remote

•

6d ago

Databricks Architect (Resident Solution Architect) - Remote Duration 8-12 months Rate DOE Experience working in the Banking Experience Core skills needed - 12-15+ years of experience in Data Engineering, Data Platforms, Data Analytics, and Modern Data Warehouse solutions, with 10+ years of overall consulting and client-facing delivery experience. - Demonstrated success delivering 6-8+ end-to-end Databricks implementations, serving as a hands-on developer, technical lead, or solution architec

Easy Apply

Contract

Depends on Experience

Databricks Architect

Remote

•

10d ago

Position: Databricks Architect (Resident Solution Architect) Location: Remote Duration: contract Rate: DOE Core skills needed - 12-15+ years of experience in Data Engineering, Data Platforms, Data Analytics, and Modern Data Warehouse solutions, with 10+ years of overall consulting and client-facing delivery experience. - Demonstrated success delivering 6-8+ end-to-end Databricks implementations, serving as a hands-on developer, technical lead, or solution architect. - Databricks Data Engineeri

Easy Apply

Contract

Depends on Experience

Solutions Architect Databricks

Remote

•

Today

Role name: Resident Solutions Architect (Databricks) Work Location: United states of America (remote) Start date: Immediate availability. Employment Type: Contract Interview Mode: Phone/Video About the job you're considering As a Resident Solutions Architect, you will serve as a trusted technical advisor and hands-on leader for enterprise data and analytics initiatives. You will partner with client stakeholders and delivery teams to design, optimize, and scale modern data platforms leverag

Easy Apply

Full-time, Part-time, Third Party, Contract

Databricks Architect

Remote or San Francisco, California

•

Today

DataBricks Architect (Resident Solution Architect ) Location: San Francisco, CA (Remote is ok if not able to find local.. need to work in PST Time Zone) Duration: 8-12 months Core skills needed: 12-15+ years of experience in Data Engineering, Data Platforms, Data Analytics, and Modern Data Warehouse solutions, with 10+ years of overall consulting and client-facing delivery experience. Demonstrated success delivering 6-8+ end-to-end Databricks implementations, serving as a hands-on developer, t

Easy Apply

Full-time, Part-time, Third Party, Contract

Job Details

Skills

Distributed Computing
Continuous Integration
Curriculum
Data Engineering
Cloud Computing
Communication
Continuous Delivery
Operational Excellence
Optimization
Performance Tuning
Machine Learning Operations (ML Ops)
Mentorship
Google Cloud Platform
IT Management
Machine Learning (ML)
Data Governance
Good Clinical Practice
Microsoft Azure
Amazon Web Services
Roadmaps
Scalability
Analytics
Apache Spark
Databricks
DevOps
RSA
Stakeholder Management
Technical Direction
Testing
Training
Resident Solutions Architect
Data Platforms
Data Analytics
Spark Architecture
Spark Runtime Internals
Cost Optimization
AWS
Azure
GCP
Cloud Architecture
Cloud-Native Technologies
CI/CD
MLOps
Machine Learning Lifecycle
Model Deployment
Data Platform Development
Production Deployment
Databricks Development
Databricks Data Engineering Professional Certification
Data Security
Reliability
Technical Architecture
Architecture Standards
Technical Roadmaps
Enterprise Data Platforms
Data Engineering Solutions
Analytics Solutions
Cloud Optimization
Platform Optimization
Technical Leadership
Consulting
Mentoring
Troubleshooting
Best Practices
Databricks Platform Capabilities
Distributed Data Processing
Data Pipelines
Cloud Data Engineering
Enterprise Architecture
Production Support
ySpark
Python
SQL
Delta Lake
Unity Catalog
Lakehouse Architecture
ETL/ELT
Spark Optimization
Databricks Workflows
MLflow
Terraform
Git
Data Quality
Google Cloud
Delta Live Tables (DLT)
Databricks SQL
Medallion Architecture
PySpark
Infrastructure as Code (IaC)
Azure Data Factory
AWS S3
Azure Data Lake Storage (ADLS)
Kafka
Data Streaming
Workflow Orchestration
Job Clusters
Serverless Compute
Cluster Optimization
Partitioning
Caching
Query Optimization
Data Modeling
Data Warehousing
Data Lake
Data Lakehouse
Data Lineage
Data Observability
Security & Access Control
RBAC
CI/CD Automation
GitHub
Azure DevOps
Jenkins
Model Monitoring
Model Lifecycle Management
Cloud Migration
Platform Modernization
Solution Architecture
Technical Roadmap
Architecture Governance
Cost Management
FinOps

Distributed Computing
Continuous Integration
Curriculum
Data Engineering
Cloud Computing
Communication
Continuous Delivery
Operational Excellence
Optimization
Performance Tuning
Machine Learning Operations (ML Ops)
Mentorship
Google Cloud Platform
IT Management
Machine Learning (ML)
Data Governance
Good Clinical Practice
Microsoft Azure
Amazon Web Services
Roadmaps
Scalability
Analytics
Apache Spark
Databricks
DevOps
RSA
Stakeholder Management
Technical Direction
Testing
Training
Resident Solutions Architect
Data Platforms
Data Analytics
Spark Architecture
Spark Runtime Internals
Cost Optimization
AWS
Azure
GCP
Cloud Architecture
Cloud-Native Technologies
CI/CD
MLOps
Machine Learning Lifecycle
Model Deployment
Data Platform Development
Production Deployment
Databricks Development
Databricks Data Engineering Professional Certification
Data Security
Reliability
Technical Architecture
Architecture Standards
Technical Roadmaps
Enterprise Data Platforms
Data Engineering Solutions
Analytics Solutions
Cloud Optimization
Platform Optimization
Technical Leadership
Consulting
Mentoring
Troubleshooting
Best Practices
Databricks Platform Capabilities
Distributed Data Processing
Data Pipelines
Cloud Data Engineering
Enterprise Architecture
Production Support
ySpark
Python
SQL
Delta Lake
Unity Catalog
Lakehouse Architecture
ETL/ELT
Spark Optimization
Databricks Workflows
MLflow
Terraform
Git
Data Quality
Google Cloud
Delta Live Tables (DLT)
Databricks SQL
Medallion Architecture
PySpark
Infrastructure as Code (IaC)
Azure Data Factory
AWS S3
Azure Data Lake Storage (ADLS)
Kafka
Data Streaming
Workflow Orchestration
Job Clusters
Serverless Compute
Cluster Optimization
Partitioning
Caching
Query Optimization
Data Modeling
Data Warehousing
Data Lake
Data Lakehouse
Data Lineage
Data Observability
Security & Access Control
RBAC
CI/CD Automation
GitHub
Azure DevOps
Jenkins
Model Monitoring
Model Lifecycle Management
Cloud Migration
Platform Modernization
Solution Architecture
Technical Roadmap
Architecture Governance
Cost Management
FinOps

Summary

Role: Resident Solutions Architect (RSA) – Databricks

Location: Remote – US
Duration: 12 Months

Role Overview:

Key Responsibilities:

Architect and deliver scalable data engineering, analytics, and data platform solutions using Databricks.
Work directly with business, client, and technical stakeholders to establish architecture standards, technical strategies, best practices, and implementation roadmaps.
Provide hands-on technical direction throughout data platform development, integration, optimization, testing, and production deployment.
Identify opportunities to improve platform performance, scalability, reliability, and cloud/Databricks cost efficiency.
Guide engineering teams in implementing CI/CD, DevOps, automation, and MLOps practices for enterprise data solutions.
Provide technical mentorship on Apache Spark, distributed processing, Spark architecture, and performance optimization.
Assess new Databricks capabilities and cloud-native technologies and recommend solutions that support business and technical objectives.
Partner with delivery teams to troubleshoot complex platform and production issues and provide architectural solutions.
Establish scalable approaches for data governance, security, reliability, and operational excellence across Databricks environments.

Required Qualifications:

7+ years of professional experience in data engineering, enterprise data platforms, analytics, or related areas.
Databricks Data Engineering Professional certification along with completion of the required Databricks training curriculum.
Demonstrated delivery of 6–8+ successful data projects, with substantial hands-on experience developing solutions within Databricks.
Strong expertise in Apache Spark and distributed computing, including Spark runtime architecture, troubleshooting, and performance tuning.
Proven ability to design and deploy modern data platforms across AWS, Azure, or Google Cloud Platform, with practical working knowledge of at least one additional cloud platform.
Experience with CI/CD pipelines, DevOps practices, automated deployments, and production-grade cloud development.
Working knowledge of MLOps, machine learning lifecycle processes, model deployment, and operationalization of ML solutions.
Strong understanding of current Databricks platform capabilities, architecture patterns, scalability, reliability, governance, and enterprise best practices.
Excellent communication and stakeholder-management skills, with the ability to operate as a trusted technical advisor for enterprise clients.

Dice Id: 90999382
Position Id: 9075764
Posted 8 hours ago

Fitment

Dice Job Match Score™

🔢 Crunching numbers...

Contact the job poster

Anchal Khapekar

Recruiter @ Aptino

View Profile

Create job alert

Never miss an opportunity! Create an alert based on the job you applied for.

Remote

•

6d ago

Easy Apply

Contract

Depends on Experience

Databricks Architect

Remote

•

10d ago

Easy Apply

Contract

Depends on Experience

Solutions Architect Databricks

Remote

•

Today

Easy Apply

Full-time, Part-time, Third Party, Contract

Databricks Architect

Remote or San Francisco, California

•

Today

Easy Apply

Full-time, Part-time, Third Party, Contract

Resident Solution Architect (RSA) - Databricks

Skills

Summary

Role: Resident Solutions Architect (RSA) – Databricks

Role Overview:

Key Responsibilities:

Required Qualifications:

Dice Job Match Score™

Anchal Khapekar

Similar Jobs

Resident Solution Architect (RSA) - Databricks

Job Details

Skills

Summary

Role: Resident Solutions Architect (RSA) – Databricks

Role Overview:

Key Responsibilities:

Required Qualifications:

Dice Job Match Score™

Anchal Khapekar

Similar Jobs