Databricks Data Science Solution Architect

Databricks Data Science Solution Architect

Location: Remote
Experience: 8+ Years
Role Type: Full-Time

Job Summary

We are looking for an experienced Databricks Data Science Solution Architect with strong expertise in Data Science, Machine Learning, Python, Databricks, MLflow, MLOps, ModelOps, and Cloud Platforms .

The ideal candidate will have hands-on experience designing, developing, deploying, and operationalizing production-grade Machine Learning and Data Science solutions on Databricks . This role requires strong Python development skills and proven experience taking ML models from experimentation and notebooks to production .

Important: This is primarily a Data Science / Machine Learning / MLOps role , not a traditional Data Engineering position.

Mandatory Skills

- 7+ years of Data Science / Machine Learning experience
- 5+ years of hands-on Databricks experience
- Advanced Python Development
- Databricks Data Science Machine Learning
- Databricks Apps
- Databricks Jobs Workflows
- Databricks Pipelines
- MLflow
- Model Serving / Serving Endpoints
- MLOps / ModelOps
- Production ML Model Deployment
- ML Lifecycle Management
- Experience with AWS, Azure, or GCP

Key Responsibilities
- Design and architect scalable Data Science, Machine Learning, AI, and Advanced Analytics solutions using Databricks.
- Develop production-quality Python-based Machine Learning applications and solutions .
- Build and deploy ML solutions using Databricks Apps, Jobs, Workflows, Pipelines, MLflow, Model Serving, Unity Catalog, and Asset Bundles .
- Transform Data Science notebooks, prototypes, and ML experiments into production-ready applications .
- Manage the complete Machine Learning lifecycle , including experimentation,



model packaging, versioning, registration, testing, deployment, serving, monitoring, and retraining.
- Implement MLOps and ModelOps best practices for scalable and reliable ML deployments.
- Develop and integrate REST APIs and application services for ML model outputs and analytical applications.
- Optimize Python and Databricks workloads for performance, scalability, reliability, and cost efficiency .
- Collaborate with Data Scientists, ML Engineers, Data Engineers, Platform Engineers, Application Developers, Security teams, and business stakeholders.
- Conduct technical design reviews and provide technical leadership and mentorship to Data Science teams.
- Establish best practices, coding standards, architecture patterns, and deployment standards for ML solutions.

Required Experience Qualifications
- Bachelor s degree in Computer Science, Software Engineering, Data Science, Statistics, Mathematics, Engineering , or a related technical field.
- 8+ years of experience across Data Science, Machine Learning, ML Engineering, Software Development, or Solution Architecture .
- 7+ years of hands-on Data Science / Machine Learning experience.
- 5+ years of experience working with Databricks Products and Platform .
- Solid hands-on Python programming and development experience.
- Proven experience building and deploying production-grade ML solutions on Databricks .




- Experience taking ML models from Jupyter/Databricks notebooks and experimentation into production .
- Strong understanding of MLOps, ModelOps, ML lifecycle management, and model deployment .
- Experience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform (GCP) .

Good to Have
- Databricks Certification
- Apache Spark / PySpark
- REST APIs / Microservices
- CI/CD - Azure DevOps, Jenkins, GitHub Actions
- Model Monitoring ML Observability
- Generative AI / GenAI / LLM Applications
- R / Posit Workbench / Posit Connect
- Enterprise Data Security Governance
- Unity Catalog
- Data Access Controls
- Insurance / Financial Services / Risk / Actuarial domain experience

Ideal Candidate Profile

The ideal candidate is a Databricks Data Scientist, ML Engineer, or Data Science Architect who has hands-on experience building and productionizing Machine Learning solutions using Python and Databricks .

Candidates should demonstrate practical experience taking a Python-based ML model or Data Science application from experimentation to production using technologies such as Databricks Apps, Databricks Jobs, Workflows, Pipelines, MLflow, Model Serving, Unity Catalog, and MLOps practices .

Candidates with primarily Data Engineering-focused Databricks experience without strong Data Science/ML and production ML deployment experience will not be the ideal fit.

Job Category: developer

Job Type: Full Time

Job Location: Remote

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Databricks Data Science Solution Architect (India)
🏢 NS Global
📍 India