Advisory Architecture · Governance · Strategy

Data Platform Advisory

Focused engagements for enterprise data teams navigating platform architecture, governance, and strategy decisions. Independent perspective — not a vendor pitch.

Helping teams build platforms they can operate, evolve, and defend to stakeholders.

Available for advisory engagements alongside full-time enterprise delivery.

Engagement types

Structured advisory for complex platform decisions.

Each engagement is scoped to a clear outcome. You get working documents and practical recommendations — not theoretical frameworks that collect dust.

Architecture Review

1–2 weeks

A focused assessment of your current data platform architecture — identifying structural gaps, governance risks, and opportunities to simplify before scaling.

Deliverables

  • Architecture assessment document
  • Risk and gap analysis
  • Prioritized recommendations with effort estimates
  • Architecture decision records (ADRs) for key choices

Azure · Databricks · Fabric · Lakehouse

Governance Design

2–4 weeks

Designing the access model, ownership patterns, naming standards, and operating rules that make your platform governable at scale — not just today, but as the team grows.

Deliverables

  • Governance framework document
  • Access and ownership model
  • Naming and tagging standards
  • Operating runbooks for platform teams

Unity Catalog · Workspace Design · Policy

Platform Strategy

Ongoing advisory

A longer-term partnership for teams navigating complex platform decisions — migration paths, vendor evaluations, capability roadmaps, and the communication that gets stakeholders aligned.

Deliverables

  • Platform capability roadmap
  • Migration or consolidation strategy
  • Stakeholder-ready architecture narratives
  • Regular advisory sessions

Enterprise · Multi-cloud · Strategy

How it works

Clear scope. Focused delivery. Clean handover.

Every engagement follows the same three-phase pattern — designed so your team can own and operate the outputs from day one.

01

Scope

We start with a short conversation to understand your platform context, constraints, and what success looks like. No proposals until I understand the problem.

02

Deliver

Focused execution against a clear scope. You get working documents, architecture decisions, and practical recommendations — not slide decks.

03

Handover

Everything is designed for your team to own and operate. Clear documentation, recorded decisions, and enough context that the work outlives the engagement.

Good fit

This works well when…

  • Your data platform is growing faster than your governance
  • You're evaluating Databricks, Fabric, or a lakehouse migration
  • Your team needs clearer architecture standards before scaling
  • Stakeholders are asking questions your current documentation can't answer
  • You want an independent perspective — not a vendor pitch

Not the right fit

Probably not right if…

  • You need hands-on engineering (building pipelines, writing Spark jobs)
  • You're looking for a full-time hire rather than advisory
  • The project scope isn't defined enough for a focused engagement yet
  • You need vendor-certified implementation support

Start

Start with a conversation.

No forms, no sales process. Send a message describing your platform context and what you're trying to solve. If there's a good fit, we'll scope something together.