6 service offerings

Databricks
Development Services

End-to-end Databricks development from pre-vetted offshore teams. Custom builds, migrations, integrations, and ongoing support.

What We Offer

Delta Lake Implementation & Optimization

Scalable Delta Lake architecture within Databricks for secure and performant data storage. Our team implements lifecycle policies, access controls, and performance optimization for your workloads.

MLflow Implementation & Optimization

Intelligent MLflow configuration to eliminate manual tasks and accelerate processes. Our Databricks experts build rule-based triggers, approval chains, and conditional logic that save your team hours every week.

Unity Catalog Implementation & Optimization

Scalable Unity Catalog architecture within Databricks for secure and performant data storage. Our team implements lifecycle policies, access controls, and performance optimization for your workloads.

Databricks Performance Tuning

Optimize query performance, indexing strategies, and caching layers within your Databricks environment. Our specialists identify bottlenecks and implement solutions that reduce response times by 50-80%.

Databricks Integration & API Development

Seamless integration of Databricks with PySpark, Spark SQL, Delta Live Tables and your broader technology ecosystem. Custom API development, data synchronization, and workflow automation.

Ongoing Support & Performance Optimization

Dedicated Databricks support team for monitoring, troubleshooting, and continuous optimization. Proactive performance tuning, security updates, and feature enhancements to keep your system running at peak efficiency.

How It Works

01

Databricks Technical Discovery

Day 1-2

In-depth assessment of your Databricks requirements, existing codebase, and technical architecture. Define project scope, milestones, Delta Lake, MLflow stack decisions, and team composition.

02

Databricks Developer Matching

Day 2-4

Hand-select Databricks engineers from our vetted bench based on your tech stack (Delta Lake, MLflow). Set up development environment, PySpark, Spark SQL CI/CD pipelines, and communication channels.

03

Sprint Planning & Databricks Architecture

Day 4-7

Establish agile sprint cadence with your team. Finalize Databricks architecture decisions, define API contracts, set up monitoring with PySpark, Spark SQL, and begin the first development sprint.

04

Databricks Development & QA

Day 7-10

Iterative Databricks development with code reviews, automated testing via PySpark, Spark SQL, and QA validation each sprint. Daily standups and weekly demos keep all stakeholders aligned.

05

Databricks Deployment & Delivery

Ongoing

Production deployment with monitoring and alerting in place. Your dedicated Databricks team continues with Delta Lake, MLflow feature development, bug fixes, and performance optimization.

What You Get

Delta Lake configuration documentation & runbook
MLflow implementation guide with best practices
Unity Catalog workflow configuration & testing report
PySpark integration specifications & test results
Spark SQL configuration & connectivity report
Production-ready Databricks codebase with test coverage documentation
Architecture documentation including system diagrams and Databricks decision records
CI/CD pipeline configuration with automated testing and deployment
Knowledge transfer sessions and technical documentation for your internal team

Ready to Build with Databricks?

Tell us your requirements and we'll match you with a pre-vetted Databricks developer. First profiles in 24-48 hours.

You're all set!

We'll send matched profiles within 24-48 hours. Check your email for next steps.

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