Lead BI Engineer

<div class="content-intro"><p>Altana is the network for trusted trade. Our AI-powered product network empowers governments and businesses to build a more resilient and secure global economy while keeping trade flowing.</p></div><h1><strong>About the Role</strong></h1> <p>You will be the founding BI Engineer at Altana, responsible for building the analytical infrastructure that enables data-driven decision-making across the entire company. This is not a reporting role that sits downstream of decisions already made—it is a foundational engineering role that will define how Altana understands its own business, customers, and products.</p> <p>You will own the full stack from data modeling and pipeline orchestration through semantic layers, dashboards, and self-service tooling. You will partner directly with engineering, product, go-to-market, and finance leadership to translate ambiguous business questions into reliable, well-modeled data products. Because you are the first hire in this function, you will also set the technical direction, tooling choices, and quality standards that future BI engineers will inherit.</p> <h1><strong>What You Will Do</strong></h1> <h2><strong>Build the BI Foundation</strong></h2> <ul> <li>Design and implement a scalable analytics data warehouse (or lakehouse) layer on top of Altana’s existing data infrastructure.</li> <li>Define the canonical dimensional model: facts, dimensions, conformed keys, and slowly changing dimensions for core business entities (customers, transactions, subscriptions, product usage, pipeline).</li> <li>Stand up and own the transformation layer (e.g., dbt) with version control, CI/CD testing, and documentation standards from day one.</li> <li>Establish a semantic/metrics layer so that “revenue,” “active customer,” and “retention” mean exactly one thing company-wide.</li> </ul> <h2><strong>Deliver Insight at Scale</strong></h2> <ul> <li>Build and maintain executive dashboards covering SaaS metrics (ARR, NRR, GRR, expansion/contraction, logo churn), product engagement, and operational health.</li> <li>Create self-service datasets and exploration environments so that PMs, GTM leads, and finance can answer their own questions without filing a ticket.</li> <li>Own data quality monitoring, alerting, and incident response for the BI layer.</li> </ul> <h2><strong>Partner Across the Business</strong></h2> <ul> <li>Act as the embedded analytics thought partner for engineering leadership, product, sales, CS, and finance—translating business context into data requirements and vice versa.</li> <li>Proactively identify trends, anomalies, and opportunities in the data; surface them before anyone asks.</l