Databricks Development

Pro

Andreas Watts

Starting at

/hr

About this service

Summary

My service delivers custom-built data solutions on Databricks, tailored to your business needs. Whether you're building new data pipelines, optimizing existing workflows, or enabling advanced analytics, I design scalable and efficient system aligned with your goals.

My focus is on creating robust, high-performance data infrastructure using best practices in data modeling, ETL development, and orchestration.

FAQs

Can you work with existing data systems?
Absolutely. I can integrate with your existing data sources (e.g., cloud storage, databases, APIs) and enhance or migrate legacy pipelines into Databricks.
Will the data pipelines be optimized for performance and cost?
Yes. I apply best practices for Delta Lake, cluster configuration, and code efficiency to ensure optimal performance and cost management.
How long does the project take to complete?
This totally depends on the scope of work. The amount of data, the complexity of the data, the amount of integrations etc.
Do you provide documentation and training?
Yes. You'll receive clear, well organised documentation, and I’m happy to provide walkthroughs or training sessions for your team if needed.
Can you help with machine learning or advanced analytics?
Definitely! I can build and deploy ML models in Databricks, set up feature stores, or help with data prep for AI/BI use cases.

What's included

Databricks Workspace Setup
Fully configured Databricks workspace with notebooks, clusters, compute, (Unity) catalog, and environment tailored to your project needs.
Data Pipeline Development
Robust ETL/ELT pipelines natively in Databricks with PySpark, notebooks and data ingestion, or with your cloud tools such as Azure Data Bricks, AWS Glue and Cloud Data Fusion to extract and move data.
Delta Lake Integration
Implement Delta Lake for fast, reliable, and ACID-compliant data storage and analytics.
Data Modeling
Design star/snowflake schemas and apply best practices to ensure high-performance querying and analytics at scale.
Data Orchestration
Design and implement reliable data workflows using Databricks Jobs, task dependencies, and integration with orchestration tools like DAGster or Prefect.
ML & AI Deployment
Build and deploy machine learning models using MLflow, feature engineering pipelines, and Databricks' collaborative notebooks for scalable AI solutions.
Cost Optimization
Audit of your current implementation to find potential cost optimisations.
Documentation & Maintainable Code
Clean, modular codebase designed for scalability, and documentation for handoff to your internal teams.