Senior Analytics Engineer
About the role
The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators and problem solvers to help us create it.
Responsibilities
- Design and implement large-scale data warehouses and data marts using Snowflake, Star, or Data Vault 2.0 schemas
- Build and maintain data transformation pipelines using SQL frameworks like dbt to abstract model code
- Write complex SQL including window functions and STRUCT/ARRAY manipulations while adhering to performance best practices
- Manage and optimize DAGs, including troubleshooting task failures and improving run times
- Implement metadata management, data lineage, and security principles such as least-privilege access
- Use a test-driven approach to design systems that trap poor quality data and trigger alerts within the data flow
- Partner and lead across multiple product team functions and domains
- Drive impact through your data vision and architecture
Requirements
- 5+ years of experience in data/analytics engineering with proficiency in Python and SQL within Snowflake
- 3+ years of experience with dbt
- Owned large-scale data projects that drove significant impact through effective cross-functional partnering
- Led the design, implementation, and monitoring of data warehouses that enable clear product-focused insights
- Expert at SQL, window functions, and query optimization for complex data manipulations
- Applied performance best practices, including partitions, sort keys, and incremental modeling
- Designed systems using test-driven approaches to ensure data quality and flow integrity
- Familiarity with ELT processes and tools to prepare and clean data for analysis
- Experience mentoring stakeholders in Data Science, Analytics, PM, and Engineering on data best practices
- Experience leveraging AI tools to transform static workflows into responsive, high-output processes
Qualifications
- A dbt certification is a plus
Benefits
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.
Pay
The anticipated base salary for this position is $130,000.00 USD to $175,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment.
Schedule
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.
Company Culture
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.