Data Engineer Consultant.
Consulting That Builds, Not Just Advises.
Two senior engineers who assess, architect, and build your data infrastructure — then document it and hand it off, so your team owns the result.
A data engineer consultant is a senior engineer you bring in to assess your data, design the right architecture, and build the infrastructure to run it — without adding a permanent hire. Our data engineering consulting services are hands-on, not advisory-only: we design and then implement, building the pipelines, warehouses, and analytics infrastructure ourselves. As two senior engineers who have done this across dozens of companies, we work 60–80 hours per month, own the outcome end to end, document everything, and hand it off so your team is never dependent on us. If you want to embed us longer-term instead, see our fractional data engineer model.
Last updated: June 2026
Why Bring In a Data Engineering Consultant?
2
Senior consultants on every engagement — the people who do the work, not a sales team
130+
Production pipelines built across dozens of client engagements
40%
Under budget on a full data platform we designed and delivered
30d
To working infrastructure — most engagements show results in the first month
Is a Data Engineering Consultant Right for You?
This is for you if
- You need senior data engineering expertise for a defined project, not a permanent headcount
- You want a consultant who builds the infrastructure, not one who only delivers recommendations
- You have a data problem — messy pipelines, no warehouse, unreliable numbers — and need it fixed properly
- You tried an agency and got junior engineers, account managers, and undocumented work
- You want strategy and execution from the same team, with a clean knowledge transfer at the end
Not the right fit if
- You only want a written assessment or roadmap with no implementation
- You need 24/7 on-call production support
- You are looking for the cheapest contractor rather than senior delivery
- You cannot provide data access or business context for the engagement
What Our Data Engineering Consulting Services Include
A full engagement, not a report. We assess where you are, design where you need to be, build it, and make sure your team can run it — Aline and Lorena, two senior consultants, end to end.
Assessment & Architecture
We start by understanding your business and your data — what you have, what is broken, and what you actually need. From there we design an architecture that fits your stack, budget, and team, without over-engineering.
Hands-On Build
We implement what we design. Pipelines, warehouse setup, source integrations, data models, and automated quality checks — built by the same senior engineers who scoped the work, so nothing is lost in a hand-off.
Documentation & Handoff
Every system 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, no lock-in.
Senior Expertise, On Demand
You work directly with us, not a rotating cast of juniors. We have built data lakehouses, warehouses, and analytics platforms for organizations from 11 to 500+ employees, and we bring that experience to every consulting engagement.
How a Consulting Engagement Works
No lengthy procurement. Three steps from first call to infrastructure your team owns.
Free Strategy Call
We review your data setup, understand your goals, and determine whether a consulting engagement is the right fit. No commitment required.
Scope and Design
We agree on the engagement tier and the first deliverable, then design the architecture and start building. Most teams see working infrastructure within the first 30 days.
Build, Document, Hand Off
We deliver production-ready systems with full documentation and 30–120 days of post-engagement support. Need ongoing work? We offer maintenance engagements too.
See our full 5-phase onboarding process for details on how every engagement begins.
Consulting Engagements in Practice
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 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 Client We Consulted For
“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.”
Need a Data Engineering Consultant?
Book a free call. We'll review your setup, talk through the problem, and tell you honestly what a consulting engagement would take.
Currently accepting 1 of 3 new clients
Common Questions About Data Engineering Consulting
What does a data engineer consultant do?
A data engineer consultant assesses your current data setup, designs the right architecture, and builds the infrastructure to run it — pipelines that move data reliably, a warehouse that centralizes it, and clean models your team can trust. Unlike an advisor who hands you a slide deck, a hands-on consultant like us owns the delivery: we build the systems, document them, and hand them off so your team can run them without us.
What is the difference between a data engineering consultant and a full-time hire?
A full-time hire is a permanent salary, benefits, and a 4–8 month recruiting cycle with the risk that they haven't built infrastructure from scratch before. A data engineering consultant brings senior expertise on demand — we've done this across dozens of companies, work 60–80 hours per month, and deliver a documented system on a fixed engagement. When the build is done, your team owns it. You get the outcome without the long-term overhead.
How is your consulting different from a data engineering agency?
Most agencies staff junior engineers at senior rates and rotate you through account managers. With us, you work directly with the two senior engineers doing the work — Aline and Lorena — start to finish. No hand-offs to someone you've never met, no black-box deliverables. Everything is documented and built so your team isn't dependent on us afterward.
How much do data engineering consulting services cost?
Our consulting engagements run 60–80 hours per month with a 3-month minimum, priced for senior-level delivery rather than a junior contractor rate. The value is getting the architecture right the first time — we've delivered full data platforms 40% under budget that run on around $12K a year. For a detailed breakdown, see our fractional data engineer cost page and our data infrastructure cost review.
Do you just advise, or do you build the infrastructure too?
We build. Advisory-only consulting leaves you with a plan and no one to execute it. We design the architecture and then implement it — setting up the warehouse, building the pipelines, connecting your sources, modelling the data, and adding quality checks. Strategy and execution come from the same team, so nothing gets lost in translation.
What should I look for in a data engineering consultant?
Look for senior-level experience with documented case studies and real results, not junior engineers learning on your budget. Ask whether they build or only advise, how they handle documentation and knowledge transfer, what happens when the engagement ends, and whether pricing is clear with no hidden fees. We wrote a detailed guide — see our blog post on what to ask a data engineer before hiring.
Related Reading
Hire a Fractional Data Engineer
The embedded, ongoing version of working with us instead of a scoped consult.
Data Infrastructure Cost
What you should actually pay to run pipelines, a warehouse, and BI.
What to Ask a Data Engineer Before Hiring
The questions that separate senior consultants from the rest.