Posting record
Open 11+ days
- Circonomit's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Circonomit, so its true age is longer.
Last checked Nov 3, 2026.
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Upload your resumeWhat it asks of you
- No visa sponsorship
What the posting discloses
Not stated: Pay, real vacancy, AI screening.
Why these three
Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.
Some employers add pay only on their own site. Check the original posting before you rule it out.
Skills mentioned
About the role
Hi, I'm Erik, CTO at Circonomit. We build the decision platform industrial companies use to plan their production. Three problems on my table right now
- Users need to explore millions of records without the UI slowing down, even while an optimization model runs over the same underlying data.
- The UI and the solver need that data in different shapes and on different timescales. Our data models and query paths have to serve both.
- Customer data arrives through ERP exports, Excel files, and CSVs. It has to become one consistent, queryable model, with each tenant's data reliably isolated.
I need someone to take the data platform and own it end to end: decide what it needs, build it, keep it running.
Our models decide what gets produced when, on which machine, and at what stock level. Every one of them runs on the data you would own.
We came out of RWTH research, raised €2.8M with Vorwerk Ventures, and have customers running on our models today. Small team, Cologne office.
Requirements
- 5+ years working on production backend or data-intensive systems.
- Recent, substantial hands-on experience writing and operating production software.
- Strong Python skills. TypeScript experience is a plus.
- Production PostgreSQL experience: multi-tenancy, migrations, and performance optimization.
- Deep SQL knowledge and experience with analytical data processing, such as columnar formats or embedded query engines. We use Parquet, Arrow, and DuckDB.
- Experience building, extending, and maintaining ETL pipelines across heterogeneous sources, including ERP exports, Excel, and CSV.
- Experience setting up and maintaining CI/CD pipelines for reliable production deployments.
- The ability to make technical decisions independently and explain the trade-offs.
- German at C1 level or above, and fluent English. Team communication is in German; code and documentation are in English.
- The right to work in Germany. We do not offer visa sponsorship.
You should enjoy turning ambiguous customer needs into clear technical priorities, rather than waiting for fully specified tasks. Priorities can change as we learn from customers; you'll work directly with me to make scope and trade-offs explicit.
Benefits
- Ownership. The whole data platform: ingestion, storage, query paths, and deployments.
- Architectural influence. You'll own the evolution of our data platform: what to keep, what to improve, and where to introduce new approaches. You'll make those trade-offs directly with me.
- Real-world impact. Customers plan their production on our models today.
- Direct collaboration. Small team, no org chart between you and the founders. Weekly feedback, both ways.
- Compensation. Competitive salary plus a VSOP package reflecting your contribution and development in the role.
- Hybrid work. We work from our Cologne office, with one to two home-office days per week. You don't need to live in Cologne, but you do need to be able to work from the office on the remaining days.
- Your setup and everyday extras. Hardware of your choice · AI tooling budget · sports membership · Deutschland-Ticket.
Process: A 20-minute call, a technical conversation, a three-hour challenge with a 45-minute walkthrough, then a conversation with the team. Two to three weeks overall, with feedback within days.
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