# Internal Data Engineer (m/w/d) at Eorbit Gmbh

> Hybrid · Germany · Unspecified · Data engineering · open. Source: https://alderhq.app/jobs/personio%3Aeorbit-gmbh%3A2707604 (read 2026-11-09).

## Facts (observed)

- Company: [Eorbit Gmbh](https://alderhq.app/companies/eorbit-gmbh)
- Location text: Leipzig; Hybrid
- Where it can be done from (inferred): Hybrid · Germany (evidence: "Location: Leipzig; Hybrid")
- Posted: 2026-07-10 (122 days ago)
- First seen by alder: 2026-11-04 · last verified: 2026-11-08
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://eorbit-gmbh.jobs.personio.de/job/2707604
- Skills listed (inferred): Python, PostgreSQL, Airflow, Snowflake, dbt, SQL

## Pay and sponsorship

- Posted pay: not posted

## Description (the employer's text)

### Your mission

- Pipelines: You connect our source systems — CRM (Pipedrive), product databases, finance systems, third-party APIs, hotel systems (Opera, SIHOT, Delphi). Ingestion, scheduling, error handling.
- Modelling: You build the transformation layer (dbt or equivalent): properly versioned, tested, documented. Staging → core → marts.
- Metrics layer: One definition per metric. You permanently end the “but my spreadsheet says 4.2” conversation.
- Data quality: Tests, freshness checks, alerting. You notice a broken pipeline before the CFO does.
- Enablement: You build models so that business teams can work self-service in the BI tool. You are not a dashboard butler.
- Reporting support: You provide the reliable data foundation for C-level and investor reporting — Finance handles interpretation.
### Your profile

- 3+ years as an Analytics Engineer, Data Engineer or BI Engineer with a strong modelling focus.
- Expert-level SQL. Not “I can do joins” — window functions, incrementality, performance.
- Experience with dbt — or a convincing explanation of how you solved it differently.
- Python for ingestion and automation.
- Experience with at least one warehouse: BigQuery, Snowflake, Redshift or Postgres-based.
- Git, code review, tests, CI. Your data models are software, not a hobby project.
- You talk to business teams and translate “can you pull me a report” into a data model.
- You have moved CRM data (Pipedrive, HubSpot, Salesforce) into a warehouse before — including the joy of historically grown custom fields.
- Experience with orchestration (Airflow, Dagster, Prefect).
- BI tooling: Metabase, Looker, Power BI.
- GDPR awareness when handling personal data — not a side note for us.
### Why us?

What that means for you: you work with AI, not despite it. People who join us give feedback that shapes product decisions — and sooner or later come to understand why one prompt works better than another.

And because we are growing fast, a lot here is still taking shape. Sometimes the honest answer is “we’re still building that.” That is exactly where the opportunity lies: you will find open space rather than finished structures, and what you build here will carry your signature.

### What we offer

- Work with real AI technology at international level — not as a pilot project, but as our business model.
- Genuine room to shape things. Your ideas do not land in a suggestion box; they land in the next iteration.
- A short path to the management team. Decisions take days, not committee rounds.
- Growth you are part of. We are building the company’s next chapter — with roles, responsibility and prospects that did not exist a year ago.
- Leipzig as your primary base, with regular time in the office and flexible remote work. Hybrid models are everyday practice here, not the exception.
- Permanent contract, full-time.
- Performance bonuses for demonstrable results.
- Multi-day team events in places that are actually fun.
### Our hiring process

- Intro interview — we get to know each other, and you learn where we stand and where we are heading.
- Case study or technical study, depending on the role — a real problem from our day-to-day that we work through together.
- Interview with your future manager and, depending on the position, with our founders.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/personio%3Aeorbit-gmbh%3A2707604 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.