Define team charters, OKRs, and strategic roadmaps aligned with company-wide goals while hiring, developing, and retaining top engineering talent
Own the end-to-end vision, architecture, and execution of the data platform from ingestion and storage to transformation, serving, and consumption layers Drive adoption of modern data stack technologies like dbt, Spark, Airflow, Snowflake, BigQuery, Databricks, and Kafka to ensure scalability, reliability, and performance
Ensure platform governance, documentation, and trust by implementing robust data quality, lineage, observability, and compliance standards in partnership with Security
Champion AI/ML infrastructure by partnering with Data Science and AI Engineering teams to power real-time and batch insights, accelerate model development, and prepare data for generative AI and traditional ML workflows
Oversee analytics engineering and BI development to deliver reliable dbt semantic models, self-serve dashboards, embedded analytics, SLAs, and a data-as-a-product mindset
Act as a strategic partner to executive leadership, translating business needs into data platform investments and collaborating across Engineering, Product, Finance, and Operations
What we’re looking for
8+ years of experience in data engineering, analytics engineering, or data infrastructure roles
3+ years of experience managing multi-team or multi-functional data organizations Deep expertise in modern data stack tools and concepts, including ELT pipelines, cloud data warehouses, dbt, orchestration frameworks, and data modeling
Proven track record of building and scaling data platforms that support AI/ML workloads, including experience with feature stores, vector search, or ML pipeline infrastructure
Strong experience with at least one major cloud data platform such as Snowflake, BigQuery, or Databricks
Demonstrated ability to recruit, develop, and retain high-performing engineers and tech leads
Excellent communication skills with the ability to translate complex technical concepts for business audiences and vice versa
While not required, these are a plus
Experience with LLM integration and generative AI infrastructure such as RAG pipelines, embedding pipelines, and prompt evaluation frameworks
Familiarity with data mesh or data product frameworks Experience in a fast-growth startup or scale-up environment
Background in analytics, business intelligence, or data science in addition to engineering
For International jobs
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. #LI-[First Name Initial][Last Name Initial]1 #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.
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, 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.
