We build the pipelines, platforms and dashboards that turn scattered operational data into something a business can run on. Batch or streaming, on Fabric, Azure, Databricks, Snowflake or AWS.
Our engineers built the change data capture pipeline that took a US government agency from eight-hour data refreshes to near real time, and deployed a full bronze/silver/gold medallion architecture across their platform.
The Data Platform Review. Two weeks, $6,000, fixed scope. We read your pipelines, your warehouse and your bills, and you get a written architecture review, a costed list of what we’d change, and the order we’d do it in.
You keep the document whether or not you work with us. If you do, the $6,000 comes off the build.
Two weeks
fixed scope
$6,000
You keep the document
Batch and real-time, medallion architecture, change data capture.
Fabric, Databricks, Snowflake, Synapse — built properly, from scratch or migrated off something that’s stopped working.
Kafka, Spark Structured Streaming, Snowpipe, Kinesis.
SQL that runs in seconds instead of minutes, stored procedures, transformation layers.
Power BI, Superset, MicroStrategy, Redash. Built with the people who’ll use them, not handed over and forgotten.
Salesforce, HubSpot, Jira, healthcare EHR systems, and yes, AS/400.
Anomaly detection, predictive diagnostics, NLP classification.
Saurav Raj Joshi holds Microsoft Certified: Fabric Data Engineer Associate (DP-700) and Fabric Analytics Engineer Associate (DP-600). Transcript on Microsoft Learn.
An engineer on your team
You need people.
Who it suits — you have the roadmap and the reviews, you’re short the person.
What you manage — the work, day to day, in your tools.
What it costs — from $6,000/month for a senior data engineer, 160 hours. Minimum 20 hours.
How it starts — a call, then one to two weeks to ramp.
A product built
You need a thing built.
Who it suits — you want the problem gone, not managed.
What you manage — the outcome. We run the build.
What it costs — $4,500 to $80,000 depending on scope. 30% up front, 40% at an agreed midpoint, 30% on delivery.
How it starts — a scoping call, then a written scope and fixed price within a few days.
A decision made
You need someone to tell you what to do.
Who it suits — you’re about to make an expensive decision and want someone with no stake in it to look first.
What you manage — everything. We don’t implement.
What it costs — architecture review from $4,000. Fractional technical lead from $3,000/month.
How it starts — a call and a look at what exists.
A single-source batch pipeline runs $4,500 to $12,000. Multi-source with real business logic, $10,000 to $30,000. A full platform build on Microsoft Fabric, Databricks or Snowflake starts around $22,000 and goes to $80,000 depending on how much of a mess we’re starting from. A senior data engineer embedded in your team is from $6,000/month at 160 hours.
Every project gets a real quote after a scoping call. These are the ranges so you know whether to bother having one.
The engineer is senior and writes the code. There’s no junior behind the invoice and no account manager on top of it.
The work happens in Kathmandu, where a senior engineer costs what a senior engineer costs there.
For comparison: a senior US contractor runs $100 to $150 an hour, and a US agency bills $150 to $225. Same seniority, different address.
| Full cloud data platform (Fabric / Databricks / Snowflake) | $22,000 – $80,000 |
|---|---|
| ETL pipeline, multi-source, complex logic | $10,000 – $30,000 |
| ETL pipeline, single source, batch | $4,500 – $12,000 |
| Data Platform Review, two weeks, fixed scope | $6,000 |
| Senior data engineer, embedded, 160 hours | from $6,000/month |
Every project here was done the way we work now: our engineers inside someone else’s team, under someone else’s NDA, through the firms that employed them. So you’ll read what was built, never who for. The rest is a conversation — ask, and we’ll go as far as each agreement allows.
Change data capture pipeline
An incremental load pipeline on Azure Data Factory and Microsoft Fabric, a change data capture pipeline that cut refresh from eight hours to near real time, and full medallion architecture across the platform.
90%
A media group's legacy SQL estate. Rewrote more than 70% of the legacy SQL and cut query execution time by 90%. Rewrote a third of the stored procedures. Built and validated about twenty new business metrics.
An advertising group's Azure migration. Migrated two business units into an Azure data warehouse, implemented the ETL business logic in Synapse, and built an automated migration pipeline with data quality monitoring on top.
A retailer's Snowflake reporting. Cut pipeline latency in Snowflake for MicroStrategy reporting and automated Snowpipe and Streams ingestion from AS/400 and Salesforce.
An industrial IoT diagnostics platform. A compressor diagnostics system with thermodynamic calculations, stage-to-stage heat propagation analysis, and anomaly detection feeding a Power BI platform.
Yes. Most of our work starts with something that already exists.
Microsoft Fabric, Azure, Databricks, Snowflake and AWS. Our lead data engineer holds both of Microsoft’s Fabric certifications.
Both. Batch and real-time pipelines, medallion architecture and change data capture, with streaming on Kafka, Spark Structured Streaming, Snowpipe and Kinesis.
A single-source batch pipeline runs $4,500 to $12,000. A full platform build on Microsoft Fabric, Databricks or Snowflake starts around $22,000 and goes to $80,000. Every project gets a real quote after a scoping call.
Sometimes no. If you’re already on Snowflake and it’s working, moving costs more than it returns. Fabric earns its place when you’re on scattered Azure services, or paying for Power BI Premium capacity you’re not using, or when one team’s data can’t reach another’s. We’ll tell you which you are.
You do. It transfers to you on final payment.
In your accounts. We work inside your cloud and your repositories, with access you grant and can revoke. We don’t take copies, and we don’t use subprocessors.
One to two weeks for an embedded engineer. A scoped build starts after a scoping call and a written scope — usually two to three weeks from first contact.
Thirty minutes. Bring the capacity bill, the pipeline that keeps failing, or the migration deadline somebody set without asking you.
We come back within one business day.
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