Hire a Fractional Data Engineer.
Get Senior Infrastructure Without the Full-Time Cost.
Two senior data engineers. 60–80 hours per month. We build it, document it, and hand it off.
Instead of spending 4–8 months recruiting a full-time engineer and hoping they have actually built infrastructure from scratch before, you bring in two senior engineers who have done this across dozens of companies. We work 60–80 hours per month, own the architecture and execution end to end, document everything, and hand it off so your team never depends on us.
Last updated: June 2026
Why Do Companies Hire Fractional Data Engineers?
0
Recruiting fees, benefits overhead, or onboarding ramp-up required
2
Senior engineers on every engagement — not juniors learning on your dime
15
Day money-back guarantee — no risk to start
30d
To working infrastructure — most teams see results in the first month
Is This You?
This is for you if
- You need production-grade pipelines but cannot justify a full-time senior hire yet
- You have outgrown manual data processes and your team is not technical enough to build infrastructure
- You tried a contractor or agency and got burned — undocumented work, broken handoffs, or junior engineers
- A founder or VP is spending hours every week pulling data instead of running the business
- You want someone who owns the outcome, not just writes code to a spec
Not the right fit if
- You need 24/7 on-call production support
- You are looking for the cheapest option — our rates reflect senior-level expertise
- You only need dashboards or reports, not infrastructure
- You cannot provide data access or business context for the engagement
What Does a Fractional Data Engineer Do?
We are not a marketplace. We are not an agency staffing junior engineers at senior rates. We are two senior data engineers — Aline and Lorena — who have built data systems together across health tech, SaaS, retail, education, and multinational organizations.
Two Senior Engineers, Not a Rotating Cast
You work directly with us — Aline and Lorena. No account managers, no hand-offs to someone you have never met. We have collectively built 130+ production pipelines, data lakehouses on AWS and BigQuery, and analytics platforms serving organizations from 11 to 500+ employees.
Architecture and Execution in One Team
We do not just draw diagrams or write tickets for someone else to implement. We design the architecture, build the pipelines, set up the warehouse, connect your sources, and get the data flowing. One team, end to end.
Everything Documented for Independence
Every system we build comes with complete documentation — architecture decisions, pipeline logic, data models, runbooks. When the engagement ends, your team or your next hire picks up exactly where we left off. No black boxes.
15-Day Money-Back Guarantee
If you are not satisfied within the first 15 days for any reason, you get a full refund. No questions asked. We take the risk so you do not have to.
How Does Hiring a Fractional Data Engineer Work?
No lengthy procurement process. Three steps from first call to working infrastructure.
Free Strategy Call
We review your current data setup, understand your goals, and determine whether fractional data engineering is the right fit. No commitment required.
Scope and Start
We agree on the engagement tier (60 or 80 hours per month), define the first deliverable, and start building. Most teams see working infrastructure within the first 30 days.
Build, Document, Hand Off
We deliver production-ready systems with complete documentation. When the build wraps, you get 30–120 days of post-engagement support depending on your plan — and if you need ongoing pipeline monitoring, new integrations, or continued optimization, we offer maintenance engagements too.
See our full 5-phase onboarding process for details on how every engagement begins.
What Hiring Us Looks Like in Practice
Replacing a Legacy ETL Tool with AWS: A SaaS Migration Case Study
Flexible office marketplace SaaS · ~150 employees · Fast-growing, investment-backed · Full Pentaho to AWS migration
6 months
to fully replace Pentaho with a modern AWS stack
4 sources integrated
PostgreSQL, Pipefy, HubSpot, Segment.io
30+ pipelines
running in Airflow
Tech: Apache Airflow · AWS Lambda · AWS S3 · PostgreSQL · Pipefy · HubSpot · Segment.io · Python · SQL · Parquet · Data Modelling
Read case study →
Building a Data Lakehouse from Scratch on AWS: A Case Study for Complex Organizations
Multinational organization · ~500 employees · $32M revenue · No prior data infrastructure
40% under budget
data platform delivered
130+ pipelines
running in Airflow across all sources
72 hours
from development to production for new pipelines
Tech: Apache Spark · Apache Airflow · Apache Iceberg · AWS · Terraform · Docker · PostgreSQL · Salesforce · Freshdesk · Google Analytics · Metabase · Python · SQL
Read case study →
From a Team That Hired Us
“The Fractional Data Engineer team worked with one of the world's largest retailers, building pipeline architecture with BigQuery, Airflow, and Looker. Strong technical execution, excellent planning, and clear communication with stakeholders. Would hire again.”
Ready to Hire?
Book a free call. We will review your setup, talk through what you need, and tell you honestly whether fractional is the right move.
Currently accepting 1 of 3 new clients
Common Questions About Hiring a Fractional Data Engineer
What is the difference between hiring a fractional data engineer and a contractor?
A contractor typically works from a task list and leaves when the tickets are done. A fractional data engineer owns the outcome — we design the architecture, build the systems, document everything, and make sure your team can maintain it independently after the engagement ends. We operate as part of your team, not outside it.
How many hours per week does a fractional data engineer work?
Our engagements run 60 to 80 hours per month, which translates to roughly 14–22 hours per week depending on your plan. This is enough to deliver meaningful infrastructure without the overhead of a full-time salary and benefits package. You get specialized senior-level expertise on demand, without the commitment, recruiting risk, or ramp-up time of a full-time hire.
How long does a typical fractional data engineering engagement last?
The minimum commitment is 3 months. Most engagements run 6–12 months depending on the scope. Some teams keep us on retainer for ongoing strategic work after the initial build is complete. Across our engagements, teams typically see working infrastructure within the first 30 days and a complete data foundation in 2–4 months.
Can I hire a fractional data engineer for a one-time project?
Yes, within the 3-month minimum. Many engagements are scoped around a specific deliverable — building a data warehouse, migrating off a legacy tool, or setting up analytics infrastructure. Once the project is delivered, you have full documentation and post-engagement support (30–120 days depending on plan) to keep things running.
What should I look for when hiring a fractional data engineer?
Look for senior-level experience (not junior engineers learning on your dime), documented case studies with real results, clear pricing with no hidden fees, and a knowledge transfer guarantee. Ask how they handle compliance, what happens when the engagement ends, and whether they document their work. We wrote a detailed guide on this — see our blog post on what to ask a data engineer before hiring.
Do you work with startups or only larger companies?
We work with companies from 11 to 500+ employees across SaaS, healthtech, fintech, education, and nonprofit sectors. Most of our clients are Series A through Series C startups and mid-market companies that need senior data engineering but are not ready to build a full internal team. Our smallest client had 11 employees; our largest data platform serves a 500-person global organization.
Related Reading
Full-Time vs. Fractional Data Engineer: A Side-by-Side Comparison
Detailed breakdown of cost, flexibility, and outcomes.
The Real Cost of Hiring a Senior Data Engineer
Salary, benefits, onboarding, and the hidden costs nobody talks about.
What to Ask a Data Engineer Before Hiring
The questions that separate senior engineers from the rest.