Senior Analytics Engineer

About the role

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.

Requirements

• 5+ years experience with data/analytics engineering
• 5+ years of experience with Python and SQL (preferably Snowflake)
• 3+ 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
• 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.

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