Senior Software Engineer, Data

Circonomit; Berlin; Hybrid; EUR 90.000 - 150.000; Vollzeit

Benefits dieser Stelle

Hybrid office (Cologne)

Competitive salary

Equity option

Deutschland‑Ticket

Small team ownership

Clear ownership of data platform

Zusammenfassung

Circonomit is building decision infrastructure for industrial companies. You will own the data platform end‑to‑end, from ingestion to fast query paths, and shape the platform layer tied to production deployments. The role emphasizes performance, correctness, and data architecture as the system scales across tenants.

You will work with Python, TypeScript, Solid.js, and Postgres on Cloudflare, in a small team with high ownership. Expect tight deadlines and meaningful impact.

Qualifikationen

• 5+ years building production backend or data‑intensive systems.
• Strong Python and TypeScript, and you want to work in both daily.
• German at C1 or better, and fluent English; team life runs in German; code/docs in English.

Aufgaben

• Own the data platform end to end: ingestion, storage, and fast queries.
• Own the platform layer: deployments and production readiness.
• Improve performance and correctness in the optimization engine with the team.
• Shape the data architecture for multi‑tenant growth over coming months.

Kenntnisse

Python

TypeScript

PostgreSQL

Distributed systems

API design

CI/CD

German C1

English fluent

Tools

Cloudflare

Solid.js

PostgreSQL

Parquet

Arrow

DuckDB

Jobbeschreibung

We are building at the edge of what optimization software can do today.

Three of the problems on our table right now:

• Millions of customer records have to stay fast on screen while an optimization model runs over the same data
• The same data has to feed an interactive UI and a solver run, in different shapes, against different latency budgets
• A customer's numbers live across several systems in several formats. They have to arrive in one consistent shape, stay fast to query, and stay cleanly separated per tenant

Nobody hands you these.

There is no one here whose job is to break the work down for you. You take the data platform, you decide what it needs, and you own it end to end.

Who we are

We build decision infrastructure for industrial companies. Our customers model their production, with its capacities, costs and constraints, and we compute the answer to "what should we do?" before the decision is made.

Our models decide how factories plan: what gets produced when, on which machine, and with how much stock. A planner acts on that answer, and it has to hold up in front of their management. The company measures the result in euros.

None of that works unless the data underneath is right, fast and complete. That part is this role.

Most optimization software fails in the same place. Not in the solver, but in the gap between what a company actually does and what the model assumes. Closing that gap is the whole company.

Founded by Dana (CEO) and Erik (CTO) out of RWTH research, backed by a €2.8M round led by Vorwerk Ventures, with customers live on our optimization models. A small team, based in Cologne.

Your mission

Hi, I'm Erik, CTO of Circonomit. This ad is specific on purpose: you should be able to tell from it whether this is your job.

Scale our data platform across multiple customers and domains. Customer data arrives in many formats from many sources; it has to land consistently, stay manageable at millions of records, and be fast to query when models and results are on screen.

The product is a data-heavy web app with a math-heavy backend: Python, TypeScript, Solid.js, Postgres, on Cloudflare. Your center of gravity is data and infrastructure, and you touch the whole stack.

We will not sugarcoat it: short deadlines, real workload, and a platform that grows while customers already run on it.

What you'll own

Nobody here will keep your queue full. There are no tickets waiting for you.

• The data platform, end to end. Ingestion, storage, and the query paths that keep millions of records fast on screen. You design it, you build it, you run it in production
• The platform layer. Infrastructure and deployments. You make the path to production work; everyone else walks it themselves and owns what they ship
• Performance and correctness in the optimization engine, together with our research engineers
• The architecture of the data side. How this gets built is decided over the coming months, and whoever starts now decides it with us

How we work

Small team, no layers. You own the process to production: you decide when your work ships, you keep it running afterwards, and you are responsible for it.

Feedback runs both ways and continuously, in daily work and in weekly one‑on‑ones. We communicate proactively and flag it early when something isn't working. Saying no is part of the job.

We review each other's code, and we like being together in the Cologne office, because the fastest conversations still happen in a room.

We are building at the edge of what optimization software can do today.

Three of the problems on our table right now:

• Millions of customer records have to stay fast on screen while an optimization model runs over the same data
• The same data has to feed an interactive UI and a solver run, in different shapes, against different latency budgets
• A customer's numbers live across several systems in several formats. They have to arrive in one consistent shape, stay fast to query, and stay cleanly separated per tenant

Nobody hands you these.

There is no one here whose job is to break the work down for you. You take the data platform, you decide what it needs, and you own it end to end.

Who we are

We build decision infrastructure for industrial companies. Our customers model their production, with its capacities, costs and constraints, and we compute the answer to "what should we do?" before the decision is made.

Our models decide how factories plan: what gets produced when, on which machine, and with how much stock. A planner acts on that answer, and it has to hold up in front of their management. The company measures the result in euros.

None of that works unless the data underneath is right, fast and complete. That part is this role.

Most optimization software fails in the same place. Not in the solver, but in the gap between what a company actually does and what the model assumes. Closing that gap is the whole company.

Founded by Dana (CEO) and Erik (CTO) out of RWTH research, backed by a €2.8M round led by Vorwerk Ventures, with customers live on our optimization models. A small team, based in Cologne.

Your mission

Hi, I'm Erik, CTO of Circonomit. This ad is specific on purpose: you should be able to tell from it whether this is your job.

Scale our data platform across multiple customers and domains. Customer data arrives in many formats from many sources; it has to land consistently, stay manageable at millions of records, and be fast to query when models and results are on screen.

The product is a data-heavy web app with a math-heavy backend: Python, TypeScript, Solid.js, Postgres, on Cloudflare. Your center of gravity is data and infrastructure, and you touch the whole stack.

We will not sugarcoat it: short deadlines, real workload, and a platform that grows while customers already run on it.

What you'll own

Nobody here will keep your queue full. There are no tickets waiting for you.

• The data platform, end to end. Ingestion, storage, and the query paths that keep millions of records fast on screen. You design it, you build it, you run it in production
• The platform layer. Infrastructure and deployments. You make the path to production work; everyone else walks it themselves and owns what they ship
• Performance and correctness in the optimization engine, together with our research engineers
• The architecture of the data side. How this gets built is decided over the coming months, and whoever starts now decides it with us

How we work

Small team, no layers. You own the process to production: you decide when your work ships, you keep it running afterwards, and you are responsible for it.

Feedback runs both ways and continuously, in daily work and in weekly one‑on‑ones. We communicate proactively and flag it early when something isn't working. Saying no is part of the job.

We review each other's code, and we like being together in the Cologne office, because the fastest conversations still happen in a room.

Requirements

Who we’re looking for

Someone who decides what needs doing when the priority is not obvious, and says so when they think we are working on the wrong thing. Someone who still builds. In a team this size, the difference between a good hire and a great one is whether we have to organize the work for you.

What you'll need

• 5+ years building production backend or data‑intensive systems
• You still write production code yourself, today. This is a senior role because of the decisions you make, not because you stopped building
• Strong Python and solid TypeScript, and you want to work in both daily
• You have extended a pipeline to a new source whose data meant something different, without rewriting it. You know which parts to make configurable and which to keep rigid
• You have made a slow query fast in production, and you can say what the bottleneck actually was rather than what you assumed it was
• Production PostgreSQL: multi‑tenant, migrations, and the performance work that comes after the schema is live
• Real SQL depth, plus hands‑on work with any of Parquet, Arrow, DuckDB or warehouse internals
• Data pipelines over heterogeneous sources, ERP exports, Excel, CSV, onto object storage, built to keep working as customers and formats grow
• Distributed systems and API design: you have debugged a failure that only showed up under real traffic, and you know why versioning and error behaviour matter before the second customer
• CI/CD pipelines you set up yourself, in a repository other people were working in
• You make the call yourself. You have worked with enough tools and approaches to know which one fits which problem
• And you can explain it afterwards. Why this one and not the other. We look at the reasoning, not at whether we would have decided the same
• You have worked in a team, not mostly alone, and you know from experience which agile practices carry their weight
• German at C1 or better, and fluent English. Team life runs in German; code and docs are English
• NRW‑based (Cologne office), optionally Munich, Stuttgart, Berlin area or else willing to work hybrid. Open to find a way if we fit

You do not need every line on that list from day one. You do need to want to own systems end to end, and to enjoy finding out how the pieces break.

Nice to have: a substantial migration you carried out end to end · telemetry and observability · Cloudflare or comparable serverless infrastructure · frontend experience, ideally Solid.js or another reactive framework · optimization or OR exposure · manufacturing or ERP data experience.

This role is not for you

If you want a clearly defined box, or work handed to you in tickets. We are a small team, pre‑Series A: structures and processes are still being built, by us and by you. Priorities shift with customers, and some weeks a deadline bends the plan.

Benefits

• Scope. One person owns the data platform. Not a slice of it inside a team of twelve. That is a function of our size, and it will not be true here forever
• Shaping. You decide how the data side gets built, together with the founders, and you live with those decisions afterwards
• Proximity. No org chart between you and the founders. Reviews go both ways, and you hear directly from customers what your work changed
• Impact you can measure. Production plans, capacities, logistics. Your work changes how a plant plans and what it spends, and the customer puts a number on that in euros
• Feedback speed. You will know where you stand. We say things out loud, we adjust, and we expect the same from you
• High stakes. Competitive salary and relevant room in the equity package (VSOP) to match your contribution and your career development
• The basics. Hardware of your choice · AI tooling budget · sports membership · Deutschland‑Ticket

Process:

a 20‑minute first call, with me or with the engineer who owns our frontend. A second conversation with the two of us together, where the technical questions get deep. Then a hands‑on challenge, about three hours of your time, followed by a 45‑minute walkthrough where you explain your solution and the decisions behind it. Finally the team, online first, then in person at the office. Both sides decide. Two to three weeks end to end, and you hear back within days after each step.

Before you decide, ask us to put you on a call with someone here who will tell you the good, the bad and the ugly. We mean it, and people take us up on it.