Data Engineering for Nonprofits.
Lean Budgets, Reliable Data.
Connect Salesforce, QuickBooks, and program tools into one place. Automate funder reporting.
Nonprofits are sitting on more data than they realize — it is just trapped in Salesforce, QuickBooks, case management tools, and spreadsheets that do not talk to each other. We connect those systems into a single automated foundation that your team can query, report from, and trust. Most builds take 2–4 months. After that, funder reports pull from the same data your program team uses daily.
Last updated: June 2026
The Nonprofit Data Problem in Numbers
76%
Of nonprofits lack a data strategy (Salesforce.org, 2021)
36%
Of organizations reported difficulties leveraging data for decision-making in 2025, up from 14% the year before (CCS Philanthropy Pulse, 2026)
60%
Risk flags among organizations with no tech staff, vs 28% for those with 10+ (NTEN Tech Accelerate)
$200K
Fully-loaded annual cost of a full-time senior data engineer — base salary (Glassdoor) plus benefits and overhead — that is 1-2 program staff positions
Is This You?
This is for you if
- Your nonprofit has data in 3+ systems that do not talk to each other
- Board reports and funder reporting take days or weeks of manual work every quarter
- Your ED or operations lead is the unofficial 'data person' on top of their real job
- You need outcomes data for grant applications but cannot compile it quickly or consistently
- You want your team to pull their own reports without depending on one person who knows where everything lives
Not the right fit if
- You need a full-time embedded engineer building features in your donor-facing product
- Your primary need is fundraising strategy or donor CRM administration — we build data infrastructure, not CRM workflows
- You need real-time data processing for life-safety applications
- Your organization has fewer than 20 people and only uses one or two tools — a spreadsheet may be enough for now
Why Do Nonprofits Need Data Engineering Instead of Another Analyst?
Most nonprofits hire a data analyst and discover there is nothing to analyze. The data is scattered, inconsistent, and unconnected. The analyst spends 60% of their time cleaning and pulling data. The real problem is not analysis — it is plumbing.
Funder Reporting on Demand
When your CRM, financial system, and program tools are connected to a single source of truth, funder reports become a byproduct of how you operate — not a two-week project every quarter. Impact metrics, outcomes trends, and compliance data are available when you need them, not after someone manually reconciles four spreadsheets.
Self-Serve Analytics for Non-Technical Staff
Program managers, operations leads, and executives should not need to write SQL or wait for someone else to pull their numbers. We set up tools like Metabase and train your team with their own data. One of our nonprofit clients went from zero analytics capability to program managers pulling their own impact reports — no SQL, no data team, no waiting.
Multi-System Consolidation
Salesforce for donors, QuickBooks for finances, a case management tool for programs, Google Sheets for volunteer hours. We connect them all into one warehouse. Your team stops reconciling numbers across tools and starts working from data they trust.
Built for Lean Budgets
We design data infrastructure that works on nonprofit budgets — open-source tools where possible, free tiers where appropriate, and architecture that keeps costs low without sacrificing reliability. One client runs their entire data foundation on the free tier of dbt Cloud and basic Metabase. No unnecessary spend.
How Does a Nonprofit Data Engineering Engagement Work?
Most nonprofits need 2 to 4 months of focused build work, then lightweight ongoing maintenance. No multi-year contracts. No bloated scope.
Audit your data landscape
We map every system your organization uses, identify what data matters for reporting and operations, and design the architecture to connect it all.
Build the data foundation
Automated pipelines, clean data models mapped to your programs and operations, quality checks, and documentation. Your team has a reliable source of truth they can build on.
Enable your team and hand off
Self-serve analytics, training sessions with your real data, and complete documentation. Your team can operate independently after the build — and if you want us to keep maintaining pipelines, adding new data sources, or supporting reporting needs, we do that too.
Questions about data access, privacy, and handoff? See the full process on our homepage.
Relevant Case Studies
Building a dbt Data Foundation from Scratch: A Case Study for Startups Without a Data Team
Health tech · ~50 employees · No data person, just a CEO, AI, and a lot of manual checks. Now 12 people rely on the same infrastructure.
0 → 1
dbt data foundation built from scratch
10 hrs/week
given back to the CEO by eliminating manual data validation
Automated
data quality checks running continuously
Tech: dbt · dbt Cloud (free tier) · PostgreSQL · Data Modelling · dbt Tests · Calculated Columns · dbt Documentation
Read case study →
Building a Self-Serve Analytics Culture with Metabase: A Case Study for Startups Without a Data Team
Health tech · ~50 employees · 11 non-technical users now making decisions from data, without asking anyone for help
0 → 1
Metabase built and adopted from scratch
11
non-technical users actively using self-serve analytics
4 departments
onboarded: marketing, sales, operations, C-level
Tech: Metabase · Metabase (basic plan) · dbt · PostgreSQL · Workshop Design · Notion · Data Governance · Self-Serve Analytics
Read case study →
From an Education Institution
“We've only been working with the FDE team for a short time, but the impact is already becoming clear. Together, we've begun building foundational data structures that will likely support our institution for years to come. The team has been highly communicative throughout the process and has consistently provided thoughtful suggestions and feedback that not only meet our needs, but improve upon them as well.”
Let's Build Your Data Foundation
Book a free call. We will review your current data setup, map your reporting needs, and outline what a lean data foundation looks like for your organization.
Currently accepting 1 of 3 new clients
Frequently Asked Questions About Nonprofit Data Engineering
How much does fractional data engineering cost for a nonprofit?
It depends on the scope. Most nonprofit engagements run 2 to 4 months of focused build work followed by lightweight ongoing maintenance — a few hours per week. You get two senior engineers who have built data foundations for organizations like yours, with complete documentation so your team is never dependent on us. Check our pricing page for current tiers and what each plan includes.
We use Salesforce, QuickBooks, and Google Sheets. Can you connect all of them?
Yes. Multi-system consolidation is one of the most common things we do. We connect your CRM, financial system, program tools, fundraising platforms, and even spreadsheets into a single data warehouse. Once connected, your team pulls from one source of truth instead of reconciling numbers across four or five tools every time someone asks a question.
Can this help with grant reporting and funder requirements?
That is one of the highest-value outcomes for nonprofits. When your data is connected and automated, funder reports become a byproduct of how you already operate — not a separate two-week project every quarter. Impact metrics, outcomes data, trend reporting — all available on demand instead of manually compiled.
Our staff is not technical. Will they be able to use what you build?
We design for this. Every dashboard is built around the questions your team actually asks — grant spending, program outcomes, donor trends — not around database tables. We run training sessions using your real data, and by the end most people can pull funder reports and program metrics on their own. No SQL, no asking IT.
What happens when the engagement ends? Will everything break?
Everything we build is yours. Full documentation, architecture decisions, data dictionaries, and runbooks. We include post-engagement email support depending on your plan. Our goal is to leave you with infrastructure your team — or your next hire — can maintain independently. No lock-in, no dependency.
We have no data infrastructure at all. Is that a problem?
Most of our nonprofit clients start exactly there. For one client, we went from nothing — no data person, no models, no documentation — to a working dbt foundation that their whole team relies on. Starting from zero is actually an advantage: no legacy mess to clean up, no bad patterns to unlearn.
Related Reading
Data Engineering for Nonprofits: Why You Need It but Should Not Hire for It
Why nonprofits need data infrastructure and why a full-time hire is not the answer.
How to Build a Data Stack from Scratch
Where to start when you have no data infrastructure at all.
How to Get Your Team to Actually Use Metabase
Strategies for driving adoption with non-technical users.