About the Role

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.

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.

What You Will Do

Build the BI Foundation

• Design and implement a scalable analytics data warehouse (or lakehouse) layer on top of Altana’s existing data infrastructure.
• Define the canonical dimensional model: facts, dimensions, conformed keys, and slowly changing dimensions for core business entities (customers, transactions, subscriptions, product usage, pipeline).
• Stand up and own the transformation layer (e.g., dbt) with version control, CI/CD testing, and documentation standards from day one.
• Establish a semantic/metrics layer so that “revenue,” “active customer,” and “retention” mean exactly one thing company-wide.

Deliver Insight at Scale

• Build and maintain executive dashboards covering SaaS metrics (ARR, NRR, GRR, expansion/contraction, logo churn), product engagement, and operational health.
• Create self-service datasets and exploration environments so that PMs, GTM leads, and finance can answer their own questions without filing a ticket.
• Own data quality monitoring, alerting, and incident response for the BI layer.

Partner Across the Business

• Act as the embedded analytics thought partner for engineering leadership, product, sales, CS, and finance—translating business context into data requirements and vice versa.
• Proactively identify trends, anomalies, and opportunities in the data; surface them before anyone asks.
• Drive alignment on KPI definitions, measurement methodology, and reporting cadences.

Set the Technical Direction

• Evaluate and recommend the BI tooling stack (visualization, orchestration, cataloging, observability) with an eye toward total cost of ownership and long-term maintainability while re-using infrastructure and tooling already part of the larger stack.
• Write the playbook: style guides, naming conventions, PR review standards, and on-call expectations for the BI function.
• Hire, mentor, and grow the BI team as demand scales.

Qualifications

Must-Haves

• 7+ years of professional experience in analytics engineering, BI engineering, or a closely related data discipline.
• Deep fluency in SQL and at least one transformation framework (dbt strongly preferred).
• Strong dimensional modeling skills: star/snowflake schemas, conformed dimensions, incremental loading patterns.
• Production experience operating a modern lakehouse stack (e.g., Snowflake/BigQuery/ Databricks),  including transformation tooling (dbt or DLT) and a BI layer (Looker, Tableau, or Sigma).
• Track record of defining and shipping company-wide KPI frameworks and executive dashboards.
• Comfort working in ambiguity: you have built a BI function (or a significant new workstream within one) from scratch before.
• Excellent communication skills—you can explain a data model to an engineer and a retention curve to a CRO with equal clarity.

Nice-to-Haves

• Experience with Python for data pipelines, scripti