Workflow architecture
Design the structure behind your Databricks delivery process, including bundle organization, environment strategy, release flow, and standards for moving changes safely through development and production.
Ryan Weiss
Weiss Data Consulting
I help Azure-based data teams build end-to-end Databricks pipelines for reporting, batch inference, and predictive modeling using Declarative Automation Bundles and Azure DevOps CI/CD.
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From repo structure to production deployment, I build workflows that are repeatable, production-ready, and easier for internal teams to operate.
About
Practical Databricks consulting for teams that need cleaner delivery and stronger production discipline.
I work with teams that have outgrown manual releases, inconsistent environments, or Databricks projects that are difficult to move safely into production.
Weiss Data Consulting LLC focuses on end-to-end Databricks delivery on Azure. That includes the repository structure, Declarative Automation Bundles (formerly Databricks Asset Bundles), CI/CD orchestration, and workflow design needed to move projects from development into dependable production pipelines.
Typical work includes reporting pipelines, batch inference jobs, predictive modeling workflows, and the automation around them. I step in when a team needs hands-on implementation, sharper release discipline, and a simpler path to operating Databricks at production quality.
Services
Hands-on support for teams building and deploying Databricks workflows in production.
The work is scoped around practical engineering outcomes: cleaner bundle structure, stronger CI/CD, and end-to-end pipelines that are easier to release and support.
Pipeline implementation
Build end-to-end Databricks pipelines for reporting, batch inference, and predictive modeling with code, jobs, dependencies, and configuration organized for real production use.
CI/CD enablement
Set up Azure DevOps pipelines, validation steps, and deployment automation so releases are repeatable, auditable, and less dependent on manual intervention.
Rates
My work is structured around a few simple engagement models designed to fit different levels of support.
Each project is scoped individually to ensure clear outcomes, predictable delivery, and transparent pricing.
Advisory engagements
$225/hr
For targeted guidance, architecture reviews, Databricks workflow audits, and CI/CD planning. Best for teams that need expert input without a full project commitment.
Scope-defined sprints
Pricing varies by scope
Short, outcome-focused engagements designed to deliver meaningful improvements in 1-2 weeks. Typical sprint outcomes include pipeline hardening, DABs adoption, CI/CD fixes, or workflow modernization.
Most clients begin with a sprint before moving into larger delivery work.
Implementation projects
Custom fixed-price proposals
For multi-week delivery work such as building DABs-structured repos, CI/CD pipelines, automated ML workflows, or production-grade Databricks architectures.
Pricing is based on scope, complexity, and timeline, and is provided after an initial discovery session.
Ongoing support
Flexible monthly retainers
For teams that need recurring engineering support, oversight, or delivery capacity. Retainers provide predictable access to expertise for continued iteration and operational stability.
Contact
If your Databricks delivery process is slowing the team down, let's fix it.
Email me with a short note about your current Databricks setup, how you deploy today, and where the workflow is breaking down. If it sounds like a fit, we can talk through scope, delivery model, and the fastest path to meaningful improvement.
Client engagements are contracted through Weiss Data Consulting LLC.