Coragrid is looking for a Software Engineer to help build our data infrastructure, data quality systems, and traceability tools for private-company intelligence.
You will build systems that help institutional investors trust private-company data with unmatched accuracy, clear source evidence, and full traceability.
Coragrid builds data infrastructure for private markets. Our goal is to bring public-market level data fidelity to private companies. We process official financials, registry filings, and web evidence while preserving the direct link to the underlying documents.
We care about speed, truthfulness, and low-friction tools. Our product is built for investment teams and technical teams that need source-linked private-company data they can trust.
Our software development culture is based on:
Clear command-line tools
Linux/Unix-based development
Avoiding unnecessary layers and abstractions
You can work from our Helsinki office at Lapinlahdenkatu 16 or remotely.
Depending on your skills and experience, you will work on core Coragrid systems such as:
High-throughput data ingestion and processing systems
Source material indexing and document pipelines
Canonical company IDs, entity resolution, and company matching
Source-linked financials, facts, and evidence trails
Internal data refinement and quality-control workflows
System reliability and self-healing workflows
This role sits between software engineering, data infrastructure, and product-quality data workflows.
The ideal candidate combines strong software engineering fundamentals with curiosity about data systems.
You do not need to already be an experienced distributed systems engineer. However, we expect you to care about clear, maintainable code, careful debugging, repeatable workflows, and systems that make data quality visible.
You should also have a basic understanding of finance theory and the kinds of company information that are valuable to institutional investors.
We also expect you to be an experienced user of AI tools, while taking full responsibility for all code you produce. In our engineering culture, one person may manage several software agents in parallel, so we stay at the forefront of advancement.
1+ years of professional software engineering, data engineering, data science, or strong equivalent (open source) project experience.
Programming fundamentals: Ability to write clear, optimized, tested code in Rust, Go, Python, TypeScript, Java, C#, Scala, or a similar language.
Data systems and databases: Experience working with structured data, SQL, data modeling, ETL/ELT workflows, and relational databases such as PostgreSQL, MySQL, or MariaDB.
Engineering workflow: Good understanding of Git, testing, code review, CI, build, deployment, logs, and monitoring.
Experience with any of the following is considered a plus:
Rust, Python, or backend services built with frameworks such as Axum, FastAPI, or similar technologies
Experience with external APIs, including REST, GraphQL, SOAP
Rust-native CLI or TUI tools
Shell-based workflows or automation for data review, operations, and quality checks
Docker, Kubernetes, AWS, or containerized deployments
Retrieval systems, vector databases, object storage, or search and indexing infrastructure
Observability and data exploration tools such as Grafana, OpenTelemetry, notebooks, or comparable systems
Basic statistics, machine learning workflows, or evaluation methods for noisy real-world data
Emacs, Vim, Arch Linux
Strong fundamentals: You can turn ambiguous data problems into clear, simple, working systems.
Data quality mindset: You care about traceability, reliable sources, idempotent writes, and clearly defined failure modes.
Backend curiosity: You want to work across services, APIs, database queries, ingestion jobs, infrastructure, and integrations.
Linux and CLI fluency: You prefer direct tools, shell workflows, logs, tests, and reproducible commands over heavy dashboards and bloat. This also makes our systems easier for AI agents to operate.
Communication: You can concisely explain what broke, what changed, what evidence you found, and what tradeoffs remain.
Systems taste: You want to build software that is fast, simple, observable, and precise for both humans and machines.
Backend: Rust, Python, FastAPI, PostgreSQL, Qdrant, Redis.
Infra: Linux, Docker, Kubernetes, AWS, and GitHub Actions.
A strong opportunity to grow as a software engineer while working on difficult, real-world data infrastructure problems in private markets.
The salary range is €2,700–4,000 per month. The final salary depends on your working hours, skills, role scope, and experience.
You will get high ownership early and work close to product direction, customer needs, and technical architecture from day one.
We review applications on a rolling basis, so we recommend applying as soon as possible. We hope the selected candidate can start on 1 August 2026. More information about the role is also available on our careers page.
This job comes with several perks and benefits
