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# Senior Data Engineer (Search)

- **Company:** Cortea AI
- **Location:** Berlin, Germany
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Automated Storage and Retrieval Systems, BigQuery, Cloud Database, Distributed Computing Environment, Python (Programming Language), Operational Databases, SQL Databases, Data Streaming, Large Language Models, Snowflake
- **Published:** June 18, 2026
- **Apply:** https://de.indeed.com/viewjob?jk=db6997d8cbb2dc9a

## About the Role

Do you have experience in SQL?, Do you have a Master's degree?, You're a builder. You write production Python. You think in pipelines and feedback loops, not notebooks. You've worked with LLM outputs in production and have strong opinions about how to make probabilistic systems measurable., * 4+ years total, 3+ shipping production data infrastructure (pipelines, warehouses, observability)

 * Strong Python and SQL. Reads code to understand data, doesn't just trust schemas
 * Has worked with LLM outputs in production. Has built or seriously used an eval framework
 * Comfortable with cloud data warehouses (BigQuery preferred, Snowflake/Redshift fine), distributed processing, batch and streaming
 * Cares about outcomes over process, clarity over frameworks
 * Comfortable with startup environment high autonomy, high ambiguity, high speed

Bonus

 * Built or seriously contributed to retrieval/RAG, document extraction, or OCR systems
 * GCP / BigQuery / Temporal experience
 * Background in audit, compliance, legal, or another document-heavy professional services domain
 * Speaks German

No one checks every box. If you've shipped retrieval systems and like owning evaluations and pipelines, let's talk.

## Description

* Create the foundation for evaluating agent performance and quality. Make probabilistic quality measurable, regression-detectable, and reproducible across model versions
 * Maintain observability of agent cost and optimizations
 * Improve document extraction and retrieval quality on the documents that matter most (financial statements, audit reports, complex tables)
 * Maintain the Data FBigQuery foundation engineers, PMs, and founders use to make decisions
 * Partner with engineering and product to turn customer feedback into measurable, shipped improvements, * Cost and quality observability on every pipeline run, alerting that catches regressions early
 * Document extraction and retrieval quality measurably better on the documents customers care about most
 * Trusted by engineers and founders to own the data foundation end-to-end


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