About GeneralMind
GeneralMind builds autonomous AI systems that operate enterprise workflows across emails, documents, ERP systems, and human decision loops. We’re building the operational layer between humans and the real economy: AI systems that don’t just assist, but actually execute work.
In less than a year, we’ve gone from 0 → dozens of enterprise customers, including DAX and NASDAQ-listed companies. We expect to grow aggressively over the next 12 months and are building a small, elite team in Berlin to help us get there.
Our team includes ex-unicorn founders, engineers who have operated systems at massive scale, and colleagues from places like Stanford, Princeton, ETH, TUM, Coinbase, McKinsey, and Razor Group.
How We Work
We are highly execution-focused and operate with a high degree of ownership and intensity.
This is an onsite role in Berlin. We believe the level of speed, collaboration, and product iteration we want is best achieved in person.
Engineering at GeneralMind is increasingly AI-native. We expect engineers to aggressively leverage AI tools and coding agents across implementation, debugging, testing, migrations, research, and operations. The goal is not to replace engineering judgment, but to amplify it. You are still expected to fully own your systems and code end-to-end.
This environment works well for people who:
- enjoy moving fast
- want significant ownership
- like hard technical problems and ambiguity
- care deeply about systems and product quality
- want to shape architecture and engineering culture early
The Role
We are looking for a Senior Data Engineer who doesn’t fit cleanly into a single box ... that’s intentional.
This role sits at the intersection of two disciplines that are rarely mastered together:
- deep production database engineering
- modern analytical/data infrastructure
Most candidates are genuinely strong in one. We are specifically looking for someone who is unusually strong in both.
You should care equally about:
- query plans and schema design
- data models and transformation layers
- operational correctness and analytical usability
- long-term maintainability and present-day speed
You’ll work directly with the founders on foundational questions around how data flows through the company, how it is modeled, and how it ultimately becomes operational leverage.
This is a role for someone who sees data systems as core infrastructure.
What you will do
- Owning PostgreSQL as a production system: performance tuning, indexing, query optimization, vacuuming, and schema evolution
- Designing data models that balance operational correctness with analytical usability
- Building robust ETL and transformation pipelines using tools like dbt
- Creating reliable KPI infrastructure and self-serve analytics foundations
- Improving observability across pipelines, transformations, and downstream data consumers
- Partnering closely with backend engineers on long-term platform and schema decisions
- Building the foundations for AI-native data systems, embedding pipelines, and evaluation datasets
What we are looking for
- Strong data engineering fundamentals and production experience
- Deep PostgreSQL knowledge and performance intuition
- Strong understanding of data modeling and long-term schema design
- Experience building reliable ETL pipelines and transformation workflows
- Comfort switching between operational backend concerns and analytical data infrastructure
- Strong ownership mentality and systems thinking
- Ability to design maintainable, observable, scalable systems
- Clear communication and engineering judgment
- Excitement about AI-native software development and modern data infrastructure
We especially value people who have a genuine “spike”, i.e. an area where they are exceptionally strong and can significantly elevate the team.
That might be:
- PostgreSQL internals and performance tuning
- data modeling and warehouse architecture
- ETL orchestration and observability
- ClickHouse or analytical systems
- AI/ML data infrastructure
- distributed data systems
- developer tooling and platform engineering
Nice-to-Haves
- Experience with dbt in production environments
- ClickHouse or analytical database experience
- AI/ML infrastructure or embedding pipeline experience
- Experience building evaluation datasets or feature pipelines
- ERP / SAP integration experience
- Supply chain or operations domain exposure
- Experience scaling multi-tenant systems
Why Join
We believe enterprise software is about to be rebuilt around autonomous systems.
Data quality, reliability, and architecture directly determine how well those systems operate. The people joining GeneralMind now will have disproportionate impact on how the company models, moves, and operationalizes data across the platform.
You’ll work on unusually hard technical problems alongside a small, highly capable team with very large ambition.
If you’re the kind of engineer who enjoys both a perfectly tuned query and a clean, reliable data pipeline, we’d love to talk.
