Analytics Engineer
Calimala partners with enterprises across the Gulf and Europe to design, build, and scale Data & AI teams. As an Analytics Engineer, you’ll join a network of practitioners who are as comfortable in SQL and dbt as they are in tools like Power BI, Tableau, or Looker—helping organizations define metrics once and reuse them everywhere.
This role sits at the heart of how data is modelled and consumed. You’ll shape the analytics layer on top of warehouses and data platforms, designing views, models, and metrics layers that power dashboards, self-service analytics, and downstream data products.
What you'll be doing
As an Analytics Engineer at Calimala, you’ll lead and support engagements where clarity and consistency of metrics really matter. One project might involve building a new dbt project and semantic layer for a data platform; another could focus on standardizing KPIs across Power BI and Tableau reports, or refactoring legacy SQL into a maintainable analytics model.
“We treat the analytics layer as a product: documented, tested, and designed so that everyone sees the same numbers for the same question.”
You’ll work closely with data engineers, analysts, and business stakeholders to understand how decisions are made and what metrics they depend on. You’ll help define modelling standards, implement tests, and design BI artefacts that sit on top of robust, well-structured data models.
Who we're looking for
You’re comfortable living in the warehouse and the BI layer. You enjoy writing clean, well-structured SQL, and you care about modelling data in a way that makes it easy for others to use—through dbt projects, metrics layers, and well-designed dashboards.
You’ve likely worked in analytics, BI, or data engineering roles and naturally gravitated towards standardizing models and metrics. At Calimala, we value depth, accountability, and partnership—you take ownership of the analytics layer and want stakeholders to trust it enough to make real decisions on top of it.
Strong SQL skills and experience working with modern data warehouses or lakehouses
Hands-on experience with dbt or similar transformation frameworks for building analytics models
Proficiency with at least one major BI tool (e.g. Power BI, Tableau, or Looker); exposure to more than one is a plus
Familiarity with metrics layers / semantic models and defining reusable KPIs and dimensions
Experience designing data models for reporting and self-service analytics (star schemas, subject-area marts, etc.)
Exposure to version control, code review, testing, and CI/CD practices in the analytics context
Ability to work with business stakeholders to translate questions into metrics, and metrics into robust models and reports
We’re looking for practitioners who see analytics engineering as building the “data product” behind every dashboard: people who care about clear definitions, repeatable logic, and making it easy for teams to trust—and use—their data.