Mid-Senior Back-End Developer

- Build and extend the metadata engine. Implement new modelling and generation
capabilities in PL/pgSQL across our Data Vault layers. This is where most of the product's
logic lives.
- Work on the code generation pipeline. Extend platform support, add generation features,
and keep the output correct and consistent across targets.
- Investigate and resolve customer-reported issues. Reproduce the problem, identify the
root cause and fix it. Analytical thinking matters more here than knowing our codebase on day
one.
- Test what you build. Test your own code and cover it with automated unit/regressions tests.
- Refactor and improve what's already there. The product is mature and carries real history.
Part of the job is paying that down deliberately — simplifying logic, improving performance on
large models, tightening error handling — without breaking customers who depend on current
behaviour.
- Take part in review and release work. Review pull requests and support releases.

– Strong SQL. You’re comfortable with complex queries — CTEs, window functions, recursive
logic, set-based thinking — and you can read a query someone else wrote and work out both
what it does and why it’s slow. Experience with stored procedures (PL/pgSQL, PL/SQL, T-SQL
or similar) is a significant plus.
– Solid Python. Practical, production Python: clear code, tests, type hints, packaging and
libraries.
– Strong analytical thinking. The ability to take a vague symptom, form a hypothesis, test it
against evidence, and arrive at a cause rather than a workaround.
– 3+ years of professional back-end or data engineering experience, including owning
features from design through to production.
– Experience working in a Scrum team — refinement, estimation, code review, and
communicating clearly about progress and blockers, across a distributed team.
– Git and pull-request-based development.
– Fluent communication in English.
Valuable, but you can learn it here:
– Data Vault 2.0, or another data warehousing architecture (Kimball, Inmon), and genuine
interest in the modelling problems.
– Experience with any of our target platforms: Snowflake, Databricks, BigQuery, Azure Synapse,
Microsoft Fabric, PostgreSQL, Oracle, SQL Server, Greenplum, AWS Redshift, SingleStore or
Apache Spark.
– ETL and orchestration tooling: dbt, Apache Airflow or Azure Data Factory.
– Code generation, template engines, parsers, or metadata-driven systems in general.
– JVM experience — some of our code runs on the JVM.
– Experience using AI coding tools such as Claude or Cursor as part of your daily workflow.

– The chance to shape security as the company’s first dedicated hire
– Remote-first work, with hybrid possible
– Private health insurance
– Company events
– A relaxed, supportive team with real freedom to propose ideas and make decisions