Clear
communication
You get regular updates on fixes, blockers, and changes to your data systems.
Fractional data engineering
Dependable data systems without hiring full-time.
Northgrain Data gives product, operations, and analytics teams senior data engineering capacity for the pipelines, integrations, and warehouse models behind daily decisions.
Your team needs data it can trust. Skip anotherhiring process.
Broken pipelines, drifting reports, and manual fixes drain time from the people who need answers. We start with the workflows causing the most pain, stabilize them, and keep improving the systems your team runs on.
2-4
weeks to visible progress
We work inside your current stack, find the bottlenecks slowing your team down, and fix those workflows first.
0
full-time hires
Bring in senior data engineering capacity while the workload is real but still too uneven for a permanent role.
Flex
Flexible capacity as priorities change
Use the retainer for the work in front of you: pipeline fixes, modeling, automation, documentation, or maintenance.
Fractional data engineering can save around $6,000/month versus a full-time hire.
Book discovery callData systems your team can operate after we ship.
Practical
documentation
We document pipeline behavior, decisions, ownership, and operating notes your team can use later.
Ongoing
maintenance
We keep data workflows healthy as product, operations, and reporting needs change.
What we do in the first 30 days
Week 1
Assess
We map your data sources, workflows, stakeholders, and failure points. Then we choose the first problems to fix.
Weeks 2-3
Stabilize
We repair broken workflows, improve existing pipelines, or build the missing pieces your team needs first.
Week 4
Document and Handoff
You get maintainable code, documented decisions, and operating context your team can use.
After 30 Days
Improve Continuously
We move to the next useful work: pipeline reliability, warehouse modeling, automation, maintenance, or handoff.
Is Northgrain Data
right for your team?
A strong fit if
You need senior data engineering before a full-time hire.
✓
Your pipelines, integrations, or warehouse models fail often enough to slow the team down
✓
Product, operations, or analytics people spend too much time fixing data by hand
✓
You need senior data engineering capacity before a full-time hire makes sense
✓
Your priorities change month to month, so fixed project scope is too rigid
✓
You want maintainable systems instead of patches no one wants to own later
Probably not a fit if
You need one-off support around the edges.
×
You only need dashboard design or spreadsheet cleanup
×
You need 24/7 incident response or on-call support
×
You cannot provide access to the systems that need assessment
×
You want a one-time handoff with no ongoing collaboration
×
You are not ready to involve product, operations, analytics, or engineering stakeholders
Stack we ship
in production.
dbt, Snowflake, Airflow, Python, AWS, and GCP.
Tool choices based on your architecture.
Fractional retainer capacity open
Talk through the
data engineering work
your team needs next.
In a discovery call, we review your current stack, the workflows causing friction, and the first fixes worth making.
You leave with a recommendation, a likely engagement shape, and practical next steps.
No long sales process. A direct conversation about your data systems and whether this model fits.
Choose the monthly
capacity your workload needs.
Start with the level of support your current data work can absorb.
PLAN 40
Stabilize
40 hours/month
Focused data engineering capacity for teams that need to fix the most painful workflows first.
Best for: Teams with a few painful data issues and a clear first workstream.
One primary workstream
Pipeline fixes, data source integration, or warehouse modeling
Daily async updates
Practical documentation
15 days of post-engagement support
One senior data engineer
Get quote
Extra capacity available as needed
PLAN 80
MOST POPULARScale
80 hours/month
More monthly capacity for teams working across pipelines, models, automation, and maintenance.
Best for: Teams with ongoing data engineering needs across several priorities.
Multiple active workstreams
Pipeline reliability, warehouse modeling, and workflow automation
Daily async updates
Practical documentation
30 days of post-engagement support
One senior data engineer
Get quote
Extra capacity available as needed
PLAN PRO
TEAM MODEAccelerate
80 hours/month
Team-based data engineering capacity for larger initiatives or parallel workstreams.
Best for: Teams that need faster delivery, parallel workstreams, or more complex implementation.
Complex or parallel workstreams
2+ data engineers for faster delivery
Pipeline, integration, modeling, and automation support
Daily async updates
Practical documentation
45 days of post-engagement support
24h response window
Get quote
Extra capacity available as needed
Discovery calls cover fit, scope direction, and the next useful step.