Data Pipeline Audit + 30-Day Fix Plan

$8,500 · 2 weeks · Fixed fee

A senior engineer reviews your data pipelines end-to-end, identifies the bottlenecks that are costing you money, and hands you a prioritized 30-day execution plan. No fluff, no slideware — a working roadmap your team can ship against.

Who this is for

You're running a data platform that mostly works, but you know it's leaking. Maybe pipelines are slow, costs are climbing, schema drift is a recurring fire, your team is firefighting instead of building, or you're not sure whether the architecture you have can carry you through the next 12 months.

You don't need a 6-month consulting engagement. You need a senior set of eyes on the system and a concrete plan.

Best fit:

• Mid-market companies running data pipelines on AWS, Azure, or GCP
• Teams using Python, PySpark, Airflow, dbt, Snowflake, Redshift, Databricks, or Palantir Foundry
• Engineering leaders who inherited a system and need an outside read
• Companies considering a re-platform and want a sanity check before committing

Not a fit:

• You need someone to write code for you (this is an assessment, not implementation)
• You're pre-data-platform — no pipelines exist yet
• You want a vendor recommendation (this is platform-agnostic)

What you get

Week 1 — Discovery and assessment

• Kickoff call to align on scope and access
• Pipeline architecture review (code, configs, infrastructure-as-code, orchestration)
• Cost and performance analysis across your data stack
• Interviews with 2–4 engineers on your team
• Review of monitoring, alerting, and incident history

Week 2 — Synthesis and plan

• Written assessment document: what's working, what's broken, what's at risk
• Prioritized list of issues ranked by impact and effort
• 30-day execution plan with specific tasks, dependencies, and owner recommendations
• 60-minute readout call with you and your team
• 30 days of email follow-up access for clarification questions

Deliverables:

1. Pipeline architecture diagram (current state)
2. Assessment report — 15–25 pages, technical and direct
3. Prioritized issue register (spreadsheet)
4. 30-day execution plan (Gantt-style or sprint-ready)
5. Recorded readout call

Process

Day 0 — Sign SOW, get access to relevant systems (read-only), schedule kickoff.

Day 1–7 — Independent assessment work. Two short syncs with your team if needed. Minimal disruption to your engineers.

Day 8–13 — Synthesis and writing.

Day 14 — Readout call and final deliverables handed over.

Days 15–44 — Email support for follow-up questions as your team executes against the plan.

Why this and not a longer engagement

Most consulting engagements are sized for the consultant's revenue, not the client's problem. A pipeline audit doesn't take 6 months. Two weeks of focused senior engineering work, done right, gives you 90% of the value of a longer engagement at 15% of the cost.

If the assessment surfaces work you want me to execute, we can scope that separately. If not, you have a plan your existing team can run with.

FAQ

What systems do you cover? AWS, Azure, GCP. Python/PySpark/SQL. Airflow, dbt, Dagster, Prefect. Snowflake, Redshift, Databricks, BigQuery, Postgres, MSSQL. Palantir Foundry. Terraform, Kubernetes, Docker. If your stack isn't here, ask — most adjacent tools are fine.

Do you need production access? Read-only access to code repos, infrastructure configs, dashboards, and logs is ideal. No write access required. I'll sign whatever NDA or access agreement your security team needs.

What if we don't like the plan? The deliverables are yours regardless. If the assessment surfaces nothing useful (rare, but possible), you've spent $8,500 to confirm your system is in good shape — which is also valuable. No refunds, but the scope is tight enough that this almost never comes up.

Can you implement the fixes? Yes, scoped separately. About half of audit engagements turn into implementation work. No pressure either way.

How soon can you start? Typically 1–2 weeks from signed SOW. Rush availability sometimes possible — ask.