You will own the data layer, evolve our BI semantic layer on a modern BI platform, and enable teams across the company to access and trust their data. Working closely with analysts and stakeholders in Operations, Product, R&D, and Customer Success, youll turn complex data into insights that drive performance and customer value.
A day in the life
Build and expand analytics data stack.
Design and maintain curated data models that power self-service analytics and dashboards.
Develop and own the BI semantic layer on a modern BI platform.
Collaborate with analysts to define core metrics, KPIs, and shared business logic.
Partner with Operations, R&D, Product, and Customer Success teams to translate business questions into scalable data solutions.
Ensure data quality, observability, and documentation across datasets and pipelines.
Support complex investigations and ad-hoc analyses that drive customer and operational excellence.
4+ years of experience as a Data Engineer, Analytics Engineer, or similar hands-on data role
Strong command of SQL and proficiency in Python for data modeling and transformation
Experience with modern data tools such as dbt, BigQuery, and Airflow (or similar)
Proven ability to design clean, scalable, and analytics-ready data models
Familiarity with BI modeling and metric standardization concepts
Experience partnering with analysts and stakeholders to deliver practical data solutions
A pragmatic, problem-solving mindset and ownership of data quality and reliability
Excellent communication skills and ability to connect technical work with business impact
