Business Intelligence Engineer, Kodify

• Experience as a BI Engineer, Data Engineer, Analytics Engineer, Data Analyst with engineering depth, or similar. Comfortable on both sides of the line
• Strong SQL, ideally PostgreSQL: complex transformations, window functions, and enough performance awareness to know why your query is slow
• Solid Python for data work: pipelines, scripting, APIs, data manipulation. You can pick up an existing ETL codebase and extend it
• Experience with dbt: models, tests, macros, and documentation, working within an existing project's conventions
• Production experience with a BI/visualization tool (Superset, Tableau, Power BI, Looker, or similar), including the modeling layer underneath it, not just the drag-and-drop
• Solid building experience using AI - understanding AI harnessing best practices such as claude.md, hooks, skills, rules, mcps, plugins etc
• Genuinely up to date on where AI is going: you follow what's changing in models, agents, and tooling, and you have opinions about what's useful versus hype. We expect you to use AI daily and to bring new ways of working to the team, not wait to be shown them
• Experience working with dimensional / analytical models and warehouses
• Comfort with Git, code review, and modern software engineering practices applied to data
• Genuine business curiosity. You want to know how the company makes money, not just what the schema looks like
• Clear communication with non-technical stakeholders. You can explain a discrepancy without hiding behind the pipeline
• Strong sense of ownership. You don't wait to be told something is broken
• A team player who likes to help others and solve problems together
• Investigation of new technologies
• You have a real 'Can Do' work ethic - We are results-based, not clock-based!
• You love to have fun while you work!

Desirable

• At Kodify, data is at the heart of how we make decisions
• From product and marketing to finance and operations, every team relies on trustworthy data delivered at the right time
• We're looking for a BI Engineer to sit exactly where the technical and the analytical meet — building the models and pipelines that produce the numbers, and the reporting and analysis that make those numbers useful to the business
• You'll work on a data platform that supports products serving close to 100M unique visitors a month
• Reporting & dashboards - Design and own dashboards that people actually use to make decisions. Not screenshot factories, living products with an owner and a purpose
• Analysis - Answer real business questions end to end: LTV and retention, subscriptions, sales volume and take rate, production and content performance. Find the "why" behind the number, and say so clearly
• Modeling - Build and maintain dbt models, staging through marts. Conventions, tests, and documentation included, not bolted on later
• Pipelines - Work on our Python ETL: ingestion from billing APIs, Postgres, MongoDB, and our columnar layer. Build new sources, fix what's fragile, and improve error handling and observability
• Quality - Test your own work and validate numbers before a stakeholder does. If a dashboard is wrong, you care
• Stakeholders - Translate vague asks into scoped questions. Push back on requests that shouldn't be built, and propose the version that should
• Enablement - Help business teams answer their own recurring questions, so capability moves out of BI rather than piling up inside it
• Duties - Becoming a valued team member, providing feedback about tech, development lifecycle and processes. Take ownership of your code / task / role
• Goal - Be the reason the business trusts its numbers — and be one of the driving forces behind always making it better
• We're very flexible about when you get your work done, but we do have some core hours where we like to overlap in order to promote collaboration and low-latency communication between team members (10:00 to 15:00 CET/CEST). Our daily virtual stand-ups are important for us but other than that, you're free to manage your own time