Who we are
Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working and playing remarkable - giving us back our most valuable asset, time.
What you'll do
Metropolis is seeking a Staff Analytics Engineer to join our Data Engineering and Analytics team. The ideal candidate will possess a passion for creating value using data and a strong foundation in all aspects of analytics engineering. In this pivotal role, you will be instrumental in making data accessible and actionable, facilitating informed decision-making throughout the company. You will partner and lead across multiple product team functions and domains and drive impact through your data vision and architecture.
What we're looking for
- 7+ years experience with data/analytics engineering
- 7+ years of experience with Python and SQL (preferably Snowflake)
- 5+ years of experience with dbt (dbt certification a plus)
- Owned large-scale data projects that drove significant impact across the company by effectively partnering with engineering, data analysts, data scientists, and other business stakeholders
- Mentored other stakeholders in Data Science/Analytics, PM, and Engineering on data best practices
- Led the design, implementation, and monitoring of large-scale data warehouses and data marts that enable clear product-focused insights
- An expert at SQL, window functions, STRUCT/ARRAY manipulation, and query optimization
- Promoted performance best practices for your tables depending on the database engine (partitions, sort keys, dist keys, clustering, incremental modeling)
- Designed systems with a test-driven approach in mind to trap bad quality data or highlight alerts as part of your data flow
- Familiarity with ELT (Extract, Load, Transform) processes and tools to prepare and clean data for analysis
- Skill in using tools like dbt to build data transformation pipelines
Our Stack
- Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
- Datastores: MySQL, PostgreSQL, Snowflake
- Cloud: AWS
- Version control: Git & GitHub
- AI Tooling: Copilot on GitHub
- Observability: Datadog
When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. #LI-SR1 #LI-Onsite