Senior Analytics Engineer
- Level
- Senior
Not stated in the posting: salary, work type, visa.
Open. First seen 26 October 2026.
About the role
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 Senior 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
- 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
- Experience leveraging AI tools to transform static workflows into responsive, high-output processes
3 Days in Office: 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.
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 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.
Metropolis's standard text
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, and pregnancy), national origin, disability, veteran status, or any other protected characteristic under federal, state, or local law.
We are committed to providing a welcoming, accessible hiring experience. If you need a reasonable accommodation for any part of the application or interview process, please reach out to us at recruiting@metropolis.io.
What this role asks for
Standard for data engineering roles
Data Warehousing · Python · SQL · Snowflake
Common in data engineering postings at any company.
80% of this description is written for the role. The rest is Metropolis's standard text, folded away below.
Compared with Metropolis's other open jobs.
The team: Data Engineering & Analytics HIRES STEADILY
This role is one of 7 open in Data Engineering & Analytics. 4 were posted in the last 30 days and the oldest in October: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Data Warehousing (7 of 7), dbt (7 of 7), Python (6 of 7), Snowflake (6 of 7), SQL (6 of 7), Airflow (5 of 7), AWS (5 of 7)
OTHER ROLES ON THIS TEAM
- Senior Data Scientist, Growth Marketing posted Oct 21
- Senior Data Scientist, Growth Marketing posted Oct 21
- Senior Data Scientist, Growth Marketing posted Oct 21
- Senior Data Scientist, Growth Marketing posted Oct 21
- Senior Data Program Manager posted Aug 18
- Senior Data Engineer posted Oct 30
From the team and dates on Metropolis's own job board.
Salary context
33 other open postings titled Senior Analytics Engineer state a salary: median USD 155,000 to USD 200,000 a year.
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