Kodify Media Group
Business Intelligence Engineer
About this role
Business Intelligence Engineer Closed 📅 Month ago 📊 Data 🔵 Mid-level Job Description Description Who are we, and why are we hiring? We’re based on over 15 years of success, producing world-class video content and building, developing, and managing a number of high-traffic websites. Our award-winning content and websites are created exclusively by us and directly for the use of millions of users worldwide. At Kodify, we’re not just pushing boundaries in online entertainment—we’re rewriting the script! Our goal is to empower our people with everything they need to pioneer innovation in our industry. Our culture is our secret sauce, and we’re committed to preserving and enhancing it every step of the way. Join our crew, where the Kodify team is not just an asset, it’s our crown jewel. We prioritize their growth and well-being above all else, ensuring they’re set up for success and always inspired to deliver their best work. As a rapidly expanding company with diverse hubs across the globe and over 20 vibrant national cultures, working with us means embracing thrilling challenges tailor-made for a star BI Engineer! 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. What will you do? 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. Requirements 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 asclaude.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