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 you'll do
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 with engineering, data science, and business stakeholders to own project scopes
Mentor others on data best practices to drive impact through your data vision
Provide architectural guidance to ensure data is accessible and actionable across the company
Drive technical excellence within the data engineering and analytics domain
What we're looking for
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
Skill in using tools like dbt to build data transformation pipelines
Experience mentoring stakeholders in Data Science, Analytics, PM, and Engineering on data best practices
While not required, these are a plus:
A dbt certification
4 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. 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. Base salary is one component of Metropolis's total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more.#LI-CM1 #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.
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. 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.
