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 doMetropolis 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
- 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
Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection
Metropolis may utilize an automated employment decision tool (AEDT) to assess or evaluate your candidacy for employment or promotion. AEDTs are used to assist in assessing a candidate’s application relative to the required job qualifications and responsibilities listed in the job posting.
As part of this process, Metropolis retains data relevant to your candidacy, including personal information, for a period that is reasonably necessary for the use of the tool. If you are hired for the position, your data may become part of your employee records.
Metropolis Technologies is an equal opportunity employer. We make all hiring decisions based on merit, qualifications, and business needs, without regard to race, color, religion, sex (including gender identity, sexual orientation, or pregnancy), national origin, disability, veteran status, or any other protected characteristic under federal, state, or local law.
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