Simpliwork LLC · Data engineering & software

Your data is in six places. We put it in one.

Simpliwork builds the intake, processing, and integration layer underneath a business — pipelines that run on schedule, record what they did, and raise a flag the moment something breaks.

ETL & data pipelines System integrations Backend services
How a typical engagement runs live
Sourcecsv · vendor feed · legacy db
Normalizevalidate · map · dedupe
Reconcilematch · flag exceptions
Destinationwarehouse · erp · accounting
Every stage is logged, re-runnable, and monitored. Exceptions surface as a report, not a silent failure.

Consulting services

Data processing, end to end

We take on the backend work most teams put off: moving information between systems, making it agree with itself, and keeping it that way.

Intake

Getting data in

Spreadsheets, vendor exports, third-party APIs, or a legacy database with no documentation. We get it into a structure your team can query and trust.

Processing

Cleanup and reconciliation

Deduplication, normalization, validation rules, and record matching across systems — with clear reporting on the rows that need a human decision.

Pipelines

ETL that keeps running

Scheduled jobs with logging, retries, and alerting, so a failed sync becomes a notification instead of a discovery three weeks later.

Integrations

Connected systems

APIs and services that link the platforms you already pay for — accounting, ERP, CRM, and internal tools — in both directions.

Also available

General software development

Data work is where we spend most of our time, but it isn't the only thing we take on. Full application builds, architecture and technical direction, and stepping in as a team lead on projects that need one — the same engineering discipline, applied to whatever the problem happens to be.

Built with

  • C# / .NET
  • Azure Data Factory
  • SQL Server
  • MySQL
  • MongoDB
  • Vue / Quasar
  • PHP
  • REST & third-party APIs

Selected work

What the work looks like

Client details are kept confidential. These are the shapes of the problems we're usually brought in for.

Ingestion & consolidation

Many providers, many formats, one table

Situation
Data arriving from multiple upstream providers in inconsistent formats — CSV, delimited text, and multi-line layouts where a single record spans several lines. Several providers sent related datasets that only made sense once joined together.
Approach
Custom parsers written as C# applets and Azure Data Factory pipelines, each handling one provider's quirks, all normalizing into a shared schema in SQL Server. Related datasets are joined during load rather than downstream.
Outcome
One consistent table the business can query, review, and build on — with new providers added as a parser rather than a rebuild.
Historical backfill

Recovering fields that were never imported

Situation
Years into a running pipeline, the client needed reporting on fields that had deliberately been skipped at import time to keep storage and processing costs down. The data existed only in the original raw files.
Approach
A Python job to read back across the full history of archived source files, extract the newly requested fields, and produce reporting output — without disturbing the production pipeline or reprocessing everything.
Outcome
Historical reporting delivered from data the client assumed was gone, and a clearer rule for what's worth storing going forward.
Integration

From processed data to daily use

Situation
Consolidated data sitting in a warehouse isn't much use if the people who need it work somewhere else all day.
Approach
Integrated the processed output into the client's existing system of record, so results appear where staff already work rather than in a separate tool nobody opens.
Outcome
The pipeline stopped being an IT project and became part of how the business runs day to day.

Ongoing ETL engagements are maintained under retainer, with new providers, format changes, and reporting requests handled as they come up.

How we work

Three stages, no surprises

Engagements are scoped before they start, and the work is documented well enough that another developer could take it over.

01

Assess

We map the systems involved, the shape of the data, and where it currently goes wrong. You get a written scope with a fixed price or an hourly estimate before any code is written.

02

Build

Development happens in short cycles with working output you can review. Nothing goes to production without logging, error handling, and a way to re-run it safely.

03

Hand off

You receive the source, deployment notes, and a runbook covering how the pipeline operates and what to do when it fails. Ongoing support is available, never required.

Engagements

Two ways to work together

Which one fits depends on the work. We'll say which we think it is on the first call.

Project

Scoped and quoted up front

Build work — a pipeline, an integration, a migration — is scoped after an initial call and quoted as a fixed price or a capped estimate. You know the number before anything starts.

Ongoing

Flat monthly retainer

Maintenance, monitoring, and changes to systems we've built run on a flat monthly rate rather than ad-hoc hours. You get a standing line to us; we keep capacity reserved for you. No stopwatch on either side.

Who you'd be working with

A small shop, on purpose

You talk to the person writing the code. Nothing gets relayed through an account manager, and nothing gets handed to someone junior after the contract is signed.

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[Your Name]
Founder · Simpliwork LLC

Fifteen years building software professionally — C#, ASP.NET, VB.NET, and PHP applications, payment processing across several providers, desktop applications, reporting in whatever format the business needed it in, and a long run of data import and processing work.

That range matters more than it sounds. Data problems are rarely just data problems; they're usually tangled up in an application, a vendor's API, a report someone depends on, or a system that was built a decade ago by someone who's long gone. Having worked across all of it means the pipeline gets designed around how the business actually operates.

Recent years have focused on ETL and integration work — Azure Data Factory, C#, and SQL Server — alongside architecture and technical leadership on teams building larger systems.

Products

Software we build and operate

Alongside client work, Simpliwork develops its own software — starting with a platform for businesses that bill by the job.

In development

Timekeeper

Job management and invoicing for service businesses. Track work as it happens, invoice directly from it, and keep your accounting current without entering the same numbers twice.

Job & time trackingLog work, materials, and hours against the job they belong to.
InvoicingGenerate invoices from tracked work and follow them through to payment.
QuickBooks syncKeep customers, invoices, and payments aligned with your books.

A hosted, multi-tenant platform. We'll email when onboarding opens — nothing else.

More products are planned. Each one starts the same way: a problem we solved for one client that turned out to be everyone's problem.

Contact

Tell us what's stuck

A short description of the systems involved and what they need to do is enough to begin. We'll tell you what it would take, and whether we're the right fit.

Every inquiry is read by the person who'd do the work — not a sales team.

Available for project and retainer work.