Software Engineer - Data Infrastructure

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Software Engineer - Data Infrastructure

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ABOUT THE ROLE

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.

WHO ARE WE

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.

HOW WE WORK

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.

WHAT YOU'LL DO

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.

IDEAL CANDIDATE

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.

BASIC QUALIFICATIONS

\* 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.

PREFERRED SKILLS AND EXPERIENCE

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