Power BI talent on your team in 7 business days, replaceable in 24 hours.
Microsoft-certified Data Analysis Expressions engineers, semantic modellers, and report developers plug into your existing team, your Git repository, and your tenant. Billable from week one. No agency layer. No statement of work renegotiations every two weeks.
Microsoft-certified Power BI engineers available this quarter
Senior Data Analysis Expressions engineers
18 available
Semantic modellers
11 available
Report developers
9 available
Fabric and data engineers
4 available
7 days
Match to start
24 hours
Replace service level agreement
PL-300
Certified
Bench refreshed weekly. Numbers reflect engineers cleared for client engagements.
The Hidden Cost of a Thin Business Intelligence Bench
Your roadmap is not slow because the work is hard. It is slow because two senior seats are empty.
Every quarter you carry an open Power BI requisition, finance still waits on Excel exports, the data warehouse still has no semantic layer, and the dashboards your chief financial officer actually asked for stay on a backlog.
A typical 90-day window with one unfilled senior Power BI seat
Recruitment drag
94 days
Average time to hire for a senior Power BI engineer in 2025.
Backlog growth
+38%
Report and dashboard backlog growth per quarter with one missing seat.
Analyst overtime
11 hours per week
Hours your existing business intelligence analysts spend on work the missing senior should own.
Decision delay
3 weeks
Average delay before a finance question becomes a published Power BI report.
Time to start
7 days
Certified engineer matched, vetted, onboarded, and committing pull requests.
Backlog burn
−46%
Reduction in published report backlog within the first 60 days of augmentation.
Reclaim analyst time
8 hours per week
Hours returned to your existing business intelligence analysts for higher-leverage work.
Question to dashboard
5 days
From finance question to a published, governed Power BI report.
Tap a label to switch the view. The toggle pauses when you interact.
A Redefine-Built Outcome
From "the report is broken again" to Data Analysis Expressions you can audit
Augmented engineers do not just close tickets. They leave your semantic model documented, your Data Analysis Expressions measures testable, your workspace governance tightened, and your in-house analysts faster than they were the month before.
Cost of an Unfilled Power BI Seat
Every week the seat stays open, you pay for it twice.
Once in lost output (reports that do not get built, decisions that do not get made), and once in overflow (your existing analysts burning hours covering the gap). Pick a scenario below or watch them rotate.
Scenarios rotate every 4 seconds. Click any scenario to pin it.
Live cost simulation
Ticking since you opened this page
Scenario 01 · One senior Data Analysis Expressions engineer missing
Estimates use United States blended cost data for senior Power BI engineers ($165k fully loaded) and a 1.4x overflow multiplier on existing analyst time. Swap in your own numbers on a capacity call.
What You Actually Get
Eight roles. One contract. Replaceable in 24 hours.
Augment your team with any Power BI role on the rail below. Each role is a fully loaded Microsoft-certified engineer, billed weekly, terminable on two-week notice, and replaceable inside 24 hours if the fit is wrong.
01DAX
Senior Data Analysis Expressions Engineer
Optimises measure code, time intelligence, and calculation groups. Owns Data Analysis Expressions standards and code review.
Performance tuning
VertiPaq optimisation
Tabular Editor scripting
02Modelling
Semantic Model Architect
Designs star schemas, role-playing dimensions, and certified datasets that scale across the business.
Star schema design
Row-level security and object-level security rules
Owns ingestion, dataflows, Lakehouse, and pipelines feeding your semantic model. SQL, Power Query, PySpark.
Dataflow Gen2
Lakehouse and Warehouse
Notebook orchestration
05Admin
Tenant and Workspace Admin
Locks down workspaces, deployment pipelines, gateways, and capacity. Owns governance and Fabric capacity tuning.
Capacity right-sizing
Deployment pipelines
Tenant settings audit
06Lead
Business Intelligence Tech Lead
Owns the roadmap inside your stand-ups. Code reviews, sprint planning, mentoring your in-house analysts.
Sprint planning
Pull request reviews
Architecture decisions
07QA
Business Intelligence Quality Assurance and Test Engineer
Reconciles report totals to the source system, automates regression tests, signs off every release into production.
Numbers reconciliation
Regression suite
User acceptance testing facilitation
08PM
Business Intelligence Project and Delivery Lead
For multi-engineer pods. Runs the engagement, reports status to your chief financial officer, escalates risk before it costs you a quarter.
Status reporting
Risk escalation
Stakeholder management
The rail auto-scrolls through all eight roles. Hover to pause. Every role is available from the same contract.
You Get
A working teammate, not a curriculum vitae
Engineer in your Slack, Jira, and Git repository from day one
Written Data Analysis Expressions, modelling, and source-control standards already in place
Weekly status report into your chief financial officer and head of business intelligence
Backup engineer briefed in parallel for continuity
Knowledge transfer documents at exit, not just code
You Skip
Months of hiring overhead
No 90-day recruitment cycle for a senior Data Analysis Expressions hire
No agency markup layered on top of contractor rates
No statement of work renegotiation when scope shifts mid-sprint
No vendor intellectual property lock-in on dashboards your team should own
No risk of a contractor disappearing mid-engagement
Proof of Work
Eight days from kick-off to first published report.
A live engagement timeline from a recent Redefine staff augmentation. Two engineers embedded with a textile manufacturer that needed Power BI capacity alongside a Navision upgrade.
1
Day 1: Capacity call
Scope, stack, must-have skills agreed in 45 minutes
Chief financial officer joins. We confirm the gap is one senior Data Analysis Expressions engineer plus one report developer for 12 weeks, with a possible extension.
2
Day 3: Match
Three candidates presented, interviews booked same day
Pre-vetted bench, not a cold curriculum vitae pile. Client meets engineers over a 30-minute working session, not a behavioural interview.
Security review, non-disclosure agreement, and master services agreement all completed in parallel. Engineers shadow a sprint planning call before code is touched.
4
Day 7: First pull request merged
Data Analysis Expressions measure refactor closes a four-week-old ticket
Time intelligence rewrite cuts a monthly close report from 40 seconds to under 5. Existing analyst signs off the pull request.
5
Day 8: First published report
Production margin dashboard goes live in the chief financial officer workspace
Replaces a manually emailed Excel that the operations director had been chasing weekly for six months.
6
Week 4: Backlog cut
Report backlog down from 41 tickets to 22
In-house analyst time freed up by 9 hours per week, redirected to a new sales-by-region semantic model.
7
Week 12: Renewal
Engagement extended for two more quarters
Chief financial officer approves a Fabric data engineer to join the pod. Knowledge transfer documents handed to the in-house team alongside continued delivery.
Textile manufacturing10,000+ stock-keeping unit catalogue
Swan
A growing textile processor running fragmented enterprise resource planning, manual Excel reporting, and limited analytical insight across Finance, Production, Sales, and Inventory.
Problem
Fragmented and slow enterprise resource planning. Data duplication, reporting errors, and no analytical layer. The team was carrying continued growth on Excel exports.
Solution
Two augmented engineers embedded alongside the Navision 2013 R2 to NAV 2016 upgrade. They built the Power BI semantic layer, unified Finance, Production, Sales, and Inventory, and replaced manual workflows with governed dashboards.
Result
10,000+
Items now reported on through one centralised Power BI layer. Operational overhead reduced, decision-making accelerated, and the platform now scales with continued textile-sector growth.
Source: Redefine engagement records. Numbers attributable to this staff augmentation engagement.
Sample Dashboards Shipped by Augmented Engineers
Manufacturing · Production Margin · 32 measuresDistribution · Sales Pipeline · 18 measuresDistribution · Inventory Health · 24 measures
Sample outputs only. Engagements run inside your tenant against your data sources, never against a partner demo workspace.
180+
Power BI engagements delivered
42
Certified business intelligence engineers on the bench
7
Days from sign-off to first pull request
24
Hour replacement service level agreement
The One Number That Matters
$0 of bench cost when the engineer is wrong for you.
Two-week notice on every contract. 24-hour replacement on every engineer. You only pay for billable, in-stack work, validated by pull requests merged into your own Git repository.
SQL Server Reporting Services migrations completed
Why Redefine Over a Typical Partner
Side by side with the default Power BI staffing model.
Most implementation partners sell you a body, mark it up, and disappear from your stand-ups. Here is the line-by-line difference, written from the perspective of an in-house business intelligence lead who has worked with both.
Typical implementation partner
Time to first pull request
4 to 6 weeks. Onboarding, security, and access reviews handled sequentially.
Engineer mismatch
Statement of work renegotiated, 30 to 45 days to swap. Billable through the gap.
Code ownership
Reports built in a partner workspace, exported as PBIX at the end of the engagement.
In-house enablement
Tacit. Your analysts pick up patterns by reading pull requests alone, no structured handover.
Status reporting
Monthly steering committee deck. Surprises arrive at quarter end.
Contract exit
Minimum 90-day notice. Penalty clauses for early end.
Billing model
Block-of-hours retainer, used or lost. Pricing opaque.
Redefine staff augmentation
Time to first pull request
Inside 7 business days. Security, access, and onboarding run in parallel.
Engineer mismatch
24-hour replacement service level agreement. No statement of work reopen, no billable transition gap.
Code ownership
All work in your Git repository, your tenant, your workspaces. You own it on day one.
In-house enablement
Written Data Analysis Expressions, modelling, and source-control standards. Pair sessions with your analysts every sprint.
Status reporting
Weekly status email to your chief financial officer and business intelligence lead. Risks raised the day they appear.
Contract exit
Two-week notice. No penalty. Knowledge transfer documents at exit.
Billing model
Weekly invoice, line-by-line. Engineer rate transparent on every line.
Adjacent Power BI Services
If staff augmentation is not quite the shape, try one of these.
The five questions every chief financial officer asks before signing.
Seven business days from signed master services agreement to the first pull request merged in your Git repository. The first capacity call happens inside 48 hours of intake. The first candidate is presented inside three business days. Tenant access, non-disclosure agreement, and security review run in parallel so onboarding does not become the bottleneck.
24-hour replacement service level agreement. You raise the concern, we present a new candidate the next business day, and onboarding for the replacement runs in parallel with the current engineer. You only pay for billable, in-stack work. No statement of work reopening, no penalty for the swap.
You do. Work-for-hire from day one. All PBIX files, semantic models, Data Analysis Expressions, deployment pipelines, and documentation live in your tenant and your repository. We never publish to a partner workspace and export at exit. If you cancel tomorrow, the work is already yours.
Weekly invoice, line by line, blended rate per engineer disclosed up front. Senior Data Analysis Expressions engineers and semantic model architects sit at the top of the range. Report developers and quality assurance engineers sit lower. No agency markup on top, no block-of-hours retainer that disappears if unused. Compared to a full-time senior hire (loaded cost, recruitment, ramp), the year-one saving averages 38%.
Every engagement ends with a structured handover: written Data Analysis Expressions standards, semantic model documentation, deployment pipeline runbooks, and a recorded walk-through with your in-house business intelligence lead. Standard exit notice is two weeks; we recommend four for a clean handover. No penalty for early end.
Yes. A typical pod is a tech lead plus two to four engineers (Data Analysis Expressions, modelling, reports, sometimes a Fabric data engineer). Pods run their own stand-ups, share a sprint board with your team, and report into a single business intelligence delivery lead. Replacement service level agreement applies per engineer, not per pod.
Is Staff Augmentation Right for You
We are not the right fit for everyone. Here is who we work best with.
Strong Fit
You probably benefit if
You already have one or two business intelligence analysts but no senior Data Analysis Expressions or modelling depth.
A senior business intelligence hire has been open more than 60 days.
You have a defined roadmap and need throughput, not strategy.
Your team uses Git, Jira, and Slack the way you would expect.
You want code in your repository and intellectual property on your side from day one.
Probably Not The Right Fit
Look elsewhere if
You have no in-house business intelligence lead at all and need someone to set strategy. Start with consulting.
You want a fixed-price, fixed-scope build. Use development services instead.
You need round-the-clock break-fix support on a live production tenant. Use managed services or service level agreement support.
You are looking for the cheapest contractor on the market, ignoring fit.
You have less than four weeks of runway and need rescue. Use the rescue services path.
A Note From Delivery
"The clients who get the most out of augmentation already know what they want shipped. They just need senior hands to ship it. We are not a strategy consultancy in disguise. If you need a roadmap, start there. If you need throughput, start here."
Not sure where you fall? Submit the form below and we will be straight with you.
Book a Capacity Call
Tell us which seat is empty.
A 30-minute call with our delivery lead. We confirm fit, the skills you need, and the shape of the engagement. No commitment. No pitch.
Capacity call within 48 hours → candidates in 3 days → first pull request merged in week one
Onboarding an augmented engineer takes 2 to 3 hours in week one: one access provisioning call, one architecture walkthrough, and Slack onboarding. We handle everything else.
Response
Within 48 hours
Candidates
In 3 business days
Engagements
180+ delivered
Code ownership
Yours from day one
Brief received
We will review your situation and book a 30-minute capacity call within the next 48 hours. The email will include a delivery lead, not a salesperson.
Stop Carrying The Open Seat
Match in 5 days. First pull request in 7.
Microsoft-certified Power BI engineers, billed weekly, replaceable in 24 hours, code in your repository from day one.
