Unlocking Insights for a Smarter Tomorrow
We're seeking an Analytics Engineer to join our team and play a pivotal role in scaling business operations and product development.
This individual will make data more accessible, reliable, and actionable across the company by working closely with cross-functional teams and stakeholders.
The ideal candidate will model data, define metrics, build reusable assets, and develop intuitive experiences around data, driving a culture of self-serve that enables teams to make informed decisions without friction.
Our modern, developer-friendly data stack is focused on semantic modeling and AI-native self-serve analytics, featuring tools like dbt, Dagster, Cube, and Hex. This engineer will help shape and evolve this stack, teaching others how to use it and contribute to it.
Responsibilities:
* Partner with data science, product development, and business stakeholders to decode their language and transform insights into infrastructure and tooling that enables a data-driven culture.
* Unleash the power of data to monitor and track the beating heart of our operations, creating eye-catching dashboards that serve as our compass and crafting strategies for expansion.
* Be the detective who spots the gaps in our product analytics data and joins forces with engineering squads to enhance product data tracking and attribution.
* Create robust testing and monitoring systems that stand as guardians of data quality, building documentation that paves the way for data accessibility to every stakeholder.
* Roll up your sleeves and contribute to the evolution of our analytics pipelines, introducing automation wherever it makes sense and breathing new life into our data pipelines and analyses.
* Lead the cause of data and data-driven decisions, empowering informed choices throughout our organization.
Requirements:
* Degree in a quantitative field such as statistics, economics, or engineering, or relevant work experience.
* 2+ years of industry experience in a similar role.
* Advanced proficiency in SQL and Python.
* Experience with ETL/ELT tools such as dbt.
* Experience with data visualization tools such as Amplitude, Hex, or similar.
* Knowledge of data warehousing concepts, big data technologies, and analytics platforms.
* Strong oral and written communication skills and ability to collaborate with and influence cross-functional partners.
* Avid learner and practical problem solver.
* Professional proficiency in English, written and spoken.