Virtual Analytics Team: The Data Roles You Need, Without Hiring Each One
A company of 30 to 300 people needs the work of a data engineer, a BI developer and an analyst, but rarely enough of any one of them to justify a salary. The usual result is one overloaded spreadsheet person, or nothing at all.
A virtual analytics team is a set of data roles covered by outside help instead of payroll. At Lightray Solutions that help is one person: Edward Pinela, MBA, a senior consultant who covers the data engineering, BI development and analysis work part-time, while the roles that need your business knowledge stay with your own people.
That is a deliberate design, not a staffing pitch. There is no bench of analysts behind this page and no rotation of juniors. What you get is the technical half of an analytics function done by someone with 20+ years and 200+ projects behind him, and a clear list of what your side owns.
The first step is a free 30-minute strategy call. Ongoing work usually runs on prepaid Power BI Flex Support blocks, from $2,500 for 20 hours at $100 to $125 an hour, and the hours never expire.
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— Quinn R., Google review
Which roles does a small company's analytics team need?
Five, though rarely five people. Someone moves data out of the CRM, ERP and accounting system; someone builds the model and reports; someone turns the numbers into answers; someone decides what each figure means; and someone keeps the source data clean. Microsoft's adoption guidance treats the last two as formal data roles.
Large companies hire for each. A company with one finance lead and a sales manager who likes spreadsheets usually has all five jobs landing on the same two people, done in whatever hours are left over. The table shows each role and who covers it in a virtual analytics team run by Lightray.
| Role | What the role does | Who covers it here |
|---|---|---|
| Data engineer | Connects the CRM, ERP and accounting data, cleans it and keeps it loading on schedule | Edward, in bursts during builds and when a new source arrives |
| BI developer (technical owner) | Builds the semantic model, the measures and the reports, and secures access | Edward; this is the core of the work |
| Analyst | Answers the questions behind the numbers and explains changes | Shared: Edward builds the analysis, your managers interpret it for the business |
| Owner of definitions | Decides what revenue, margin or an active customer means | Always stays with you |
| Data steward | Keeps records correct in the source systems | Stays with you; Edward adds exception reports that show what needs fixing |
| Platform admin | Licenses, tenant settings, user accounts, gateway server | Your IT provider or admin, with written instructions from Edward |
What can one senior consultant cover, and what should stay in-house?
The technical roles travel well; the business roles do not. Building pipelines, semantic models and reports is specialist work that a consultant can do in concentrated bursts. Deciding what counts as an active customer, or fixing the CRM records that sales reps enter wrongly, needs someone inside the company every day.
So the split is explicit from the first week:
- Covered by Edward. Data engineering (connections, Power Query, a small warehouse where needed), the semantic model and its measures, report and dashboard builds, refresh and security setup, and the analysis behind a question.
- Kept by you. The owner of definitions, who signs off what each KPI means; the data steward, who fixes records at the source; and the people who act on the numbers.
- Kept by your IT provider or admin. Licenses, tenant settings, user accounts and the machine a data gateway runs on. Edward documents what needs changing; your admin makes the change.
- Left to a specialist. Large-scale machine learning engineering or a 24/7 data platform. If you need those, you need a dedicated hire or a firm built for it, and we will say so on the first call.
Is a virtual analytics team cheaper than hiring each role?
For most small companies, yes, because you pay for the hours used rather than for four salaries. The U.S. Bureau of Labor Statistics put the median annual wage of database architects, the closest federal category to a data engineer, at $139,500 in May 2025, before benefits, recruiting and the months a search takes.
The honest limit: one consultant has finite hours. If your reporting needs a full-time person every week, part-time cover is a bridge to that hire, not a replacement for it. Our part-time data analyst page sets out the hire-or-not arithmetic for the analyst role in detail, using BLS pay data.
How does a virtual analytics team run month to month?
It starts with a short assessment of your data sources, existing reports and who currently does each role, then settles into a rhythm: a monthly priorities list agreed with your sponsor, work done in your own Microsoft tenant, and a review of what moved. Hours rise during a build and fall once reports are stable.
Everything is built in your workspaces and documented, so the work is never locked to one person's laptop and a future hire can take it over. All delivery is remote, over video and screen-share. For the Power BI side of the work there is a simple safeguard: if the first 4 hours show you don't like working with us, you get your money back. Bigger pieces, such as a data warehouse, are scoped as fixed-price projects instead of drawn from a block.
Further reading: Microsoft Learn — Fabric adoption roadmap: Content ownership and management (data roles).
Want to see which roles you actually need filled?
Book a free 30-minute call with Edward Pinela, MBA. You get an honest read on what to fix first — and if we are not the right fit, you will hear that on the call.
Frequently asked questions
Is this a staffing agency? Will other people work on our data?
No. Lightray is Edward Pinela, MBA. He does the work himself and does not hand it to subcontractors. If a job needs a skill he doesn't offer, he tells you and helps you find the right specialist rather than reselling one.
What happens when Edward is unavailable?
Everything lives in your Microsoft tenant: the models, reports, refresh schedules and the written documentation for each. Nothing depends on a file on a consultant's machine, so routine reports keep refreshing whether or not anyone is working on them that week.
Can a virtual analytics team support data science work?
Forecasting, segmentation and driver analysis built on a clean model, yes; see our [predictive analytics consulting](/predictive-analytics-consulting/) page. A company whose product depends on machine learning models in production needs dedicated engineers, and that is not this service.
When should we hire instead?
When the analytics work fills most of a week, every week, and the questions depend on daily contact with the business. A virtual team is often how companies reach that point with a clean model in place, which makes the eventual hire productive from day one.
You Won’t Get Handed Off to Junior Staff.
At most consulting firms, the senior person who sold you shows up for the kickoff — then you get handed to a team of juniors learning on your dime. That’s not how we work.
When you hire Lightray Solutions, you work directly with Edward Pinela, MBA — a principal consultant with 20+ years of experience across Power BI, web development, SEO, and CRM systems. Edward architects every engagement personally, stays involved through delivery, and answers his own phone.
Read Edward’s Full Bio“Mid-market companies deserve senior-level expertise without paying enterprise-agency prices. That’s the gap Lightray fills.”
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