Data engineering in Bengaluru
Somewhere between seed and Series B, most Bengaluru startups discover that the numbers in the board deck, the product dashboard and the finance spreadsheet do not agree. Each was built by a different person at a different time, reading from the production database directly, and the reporting queries are now slowing down the product itself. The next investor will ask for cohort metrics, and nobody wants to explain which of the three numbers is right.
We build the warehouse and pipelines that give one answer. Data comes out of production into ClickHouse, Postgres or the warehouse you already pay for, transformations are versioned in dbt, freshness is monitored and written down, and definitions such as active user or net revenue are agreed once. On FM360 we sync a third-party system every hour and verify what the reader sees, not just whether the job ran.
Bengaluru is where we live and work, so this page is less a pitch than a description of the market we see every week. The defining fact about it is that startups and global capability centres, the in-house engineering offices of foreign companies, are competing for the same engineers. A GCC can offer a larger salary, a guaranteed bonus and a stable employer. A Series A startup offers equity and a harder job. The engineer you want usually has more than one offer, a notice period to serve, and a counter-offer waiting. So the roadmap slips while the hiring plan catches up.
The companies that call us here come in a few recognisable shapes. Startups whose first backend was written by an engineer who has since left, often for one of those GCCs. SaaS companies built in Bengaluru and sold to customers in the US and Europe from the first year, now closing their first enterprise account and the feature list that comes with it. Deep tech teams in space, robotics, semiconductors and applied AI, where the core work is research or hardware and the software around it, the dashboards, device APIs and data pipelines, is nobody's job. And GCC leaders who need a working proof of concept before headquarters will approve the headcount to build the real thing.
What they need built is usually a defined piece rather than a whole product. A backend mapped, documented and made safe to change. Single sign-on, custom roles and tenant isolation for the enterprise deal. A device API and a dashboard for a robotics team whose engineers would rather be working on the robot. A proof of concept a GCC can demo to its parent company. We build those in your repository, in increments that ship, and write the architecture notes and runbooks as we go, so whoever you hire next can read them in their first week.
We share your time zone, so the working day is the same on both sides and a question asked in the morning is answered in the morning. Because we are in the same city, a kickoff or an architecture session can happen at your office rather than on a call. Most of the work still happens in writing, in your repository and your chat, because a decision written down survives the people who made it.
We are the right fit when you have a defined piece of work and want a senior engineer on it this month rather than after a hiring round. Start with a fixed-price two-week piece and judge us on what ships. We also cover the months before your next hire joins, and work white-label for Bengaluru agencies under your name.
Four ways this arrives.
Two definitions of the same metric, computed in two places. We pick one, write it as a tested model in version control, and point every report at it, so the argument moves from whose number is right to what the definition should be.
A job reports success while the report still shows yesterday. We give every table a written freshness guarantee, monitor what the reader actually sees rather than the job that feeds it, and alert a person when the guarantee is missed.
A CRM, an ERP or a work-order tool reachable only through its API. We build the sync with retries, rate limits and normalisation at the boundary, and keep append-only snapshots so last Tuesday is a query rather than a restore.
Analytical queries running against the application database at the worst possible moment. We move them to a columnar store, keep Postgres for transactions, and feed one from the other by change data capture or scheduled extracts, whichever the freshness requirement calls for.
A nightly work-order extract into append-only ClickHouse snapshots, with a verifier that reads the live Tableau dashboard to prove it shows the newest data.
Read the write-up →Asked by Bengaluru teams.
Can we meet in person?+
Yes. We are in Bengaluru, so a kickoff, a design review or a whiteboard session at your office is easy to arrange. We share your time zone, so calls happen inside your normal working day. Day to day we work in your tools, Slack, GitHub and Linear or whatever you already use, and you talk directly to the engineer writing the code. In-person time is best spent on the first architecture discussion and the handover.
Do you build for Bengaluru SaaS companies selling abroad?+
Yes, and it is one of the most common pieces of work we see here. We build what the first overseas enterprise customer asks for: single sign-on, custom roles, tenant isolation that holds under a missing filter, a log of who changed what, and billing through Stripe that copes with several currencies. The work happens inside your product, in increments that ship, so the deal keeps moving while the list gets shorter.
How does your rate compare to hiring in Bengaluru?+
PayScale puts a mid-career software engineer in Bengaluru at about ₹18 lakh a year. Our published rate is $35 an hour, with a $5,000 minimum. For that you get a senior engineer who writes the code, works in your Slack, GitHub and Linear, and starts within days, with no recruiting round, notice period or employment overhead. Begin with a fixed-price two-week piece at $2,800 and judge us on what ships.
We keep losing engineers to GCCs. How can you help?+
We add senior capacity while you rebuild the team. An engagement starts within days, so the roadmap keeps moving through the notice periods and counter-offers. We take a defined piece of work, ship it in your repository, and write the architecture notes and runbooks your next hire reads in their first week. The code belongs to you from the first commit, so picking it up later is a conversation, not a project.
Do we need a data warehouse yet?+
Maybe not. If your reporting runs comfortably against a Postgres read replica, a warehouse adds a second system to pay for and keep in step. The signs you need one: analytical queries slowing the product, data from several sources that has to be joined, or history you must keep that the application overwrites. We will tell you which side of that line you are on.
Why ClickHouse rather than Snowflake or BigQuery?+
Not always. For steady, high-volume analytical work, ClickHouse is fast and cheap to run, self-hosted or on its managed cloud, and we run it in production. Snowflake and BigQuery ask less of you operationally and suit ad hoc querying across a large team. If nobody on your side wants to operate a database, we will recommend the managed option even when the invoice is larger.
What does a freshness guarantee actually mean?+
A written statement per table or report, such as "never more than an hour behind" or "reflects yesterday's close by 07:00". Each one has a check that measures it and an alert that fires when it is missed. Without it, stale data looks exactly like correct data until somebody makes a decision on it.
Can you work with the tools we already have?+
Usually, yes. If you already run dbt, Airflow, Fivetran or a BI tool your team knows, we build inside it. We suggest replacing a tool only when it is the cause of the problem you hired us for, and we show you the evidence before asking you to fund a migration.
How do you handle personal data in the warehouse?+
We decide what should reach the warehouse at all before building the pipeline. Identifiers can be hashed or tokenised at ingestion, sensitive columns restricted by role, and retention enforced by the pipeline itself. Every field is documented from source to dashboard, so anyone can see where a number came from and who can read it.