Data engineering in Pune
Ask three people at a Pune plant for last week's output and you may get three answers: one from the machines, one from the manufacturing execution system and one from the supervisor's shift register. Overall equipment effectiveness is calculated differently at each plant, downtime reasons are chosen from lists nobody maintains, and the monthly management report is assembled by hand from exports.
We build the data platform that gives one answer. Machine and system data is pulled on a schedule into ClickHouse, which handles high-volume time-series well, or into the warehouse you already use, and joined with the ERP. Definitions of output, downtime and effectiveness are agreed once and versioned, so every plant is measured the same way. Freshness is shown next to every number, and dashboards read from the warehouse, not from production systems on the floor.
Pune runs two economies inside one metropolitan area. It is one of India's most important automobile and manufacturing hubs, with plants in Chakan, Pimpri-Chinchwad and Talegaon; Chakan alone hosts vehicle plants for Mercedes-Benz, Volkswagen, Bajaj Auto, Mahindra and Jaguar Land Rover, surrounded by hundreds of component suppliers. It is also one of the country's largest IT hubs, spread across Hinjewadi, Kharadi, Baner and Viman Nagar. And it makes vaccines: the Serum Institute of India, the world's largest vaccine manufacturer, is here too.
The most interesting software problems sit where those economies meet. Carmakers expect their suppliers to exchange schedules, shipping notices, drawings and quality documents electronically, and to keep up when the format changes. Plants want to know why a line stopped, which machine keeps failing and what the real output was per shift, but the data sits in machine controllers, a manufacturing execution system, an ERP and a supervisor's register, none of which agree. Industrial software startups, often founded by engineers who know those plants from the inside, are building products to fix exactly that, and selling them in India and abroad.
Our place is the software above the machines, working alongside your automation partner. We build the integrations that read what your machines and systems already expose, the data pipelines and dashboards that turn it into one picture, the supplier portals, the mobile apps for technicians and inspectors, and the SaaS products that package all of it. Pune also has a deep bench of IT services and engineering services firms, and a firm like ours can take a specialist piece of their larger programme, delivered under their name.
We are in Bengaluru and share your time zone, so the working day is the same on both sides and a problem raised in the morning gets a response that morning. Most of the work runs through your repository and a shared chat channel, and you talk directly to the engineer who writes the code. What we learn about your process, from calls, documents and photos of the floor, is written down as we go, so everyone works from the same picture.
We are the right fit for a defined build, an integration with an end date, or a product that needs to reach its first pilot plant before your own team is hired. Start with a fixed-price two-week piece and judge us on what ships. Pune's IT services and engineering firms can also bring us in white-label, under their 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 Pune teams.
How do you work with teams in Pune?+
We are in Bengaluru and share your time zone, so calls, reviews and releases fit inside your normal working day. We work in your tools, Slack, GitHub and Linear or whatever your team already uses, and you talk directly to the engineer writing the code. Photos, short videos and a walk-through call from the floor go a long way, and everything we learn is written into your repository as runbooks and architecture notes.
Can you connect to our machines and plant systems?+
Yes, through the data they already expose. We integrate with what your manufacturing execution system, historian, SCADA or machine gateways publish, whether that is a database, an API, a message broker or exported files, and build the pipelines, dashboards and apps on top. We work alongside your automation partner, who looks after the controllers, and help you specify any new data points worth adding to the line.
How does your rate compare to hiring in Pune?+
PayScale puts a mid-career software engineer in Pune at about ₹14 lakh a year. Our published rate is $35 an hour, with a $5,000 minimum. That buys 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.
Can you work white-label for our IT services firm?+
Yes. Work ships under your name, in your client's repositories and through your delivery process, and we sign an NDA before specifics. We stay behind your team unless you want us in the room. It works best for a well-defined specialist piece inside a larger programme, such as a data pipeline, a mobile app or an infrastructure migration, and the code belongs to your client from the first commit.
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.