Analytics Engineer
Bridge33 Capital
Bridge33 is looking for an Analytics Engineer to help build and maintain the datasets that power decision-making across the business. You'll work at the center of our data platform modeling raw data from our property management and financial systems into clean, tested, well-documented sources of truth, and delivering reporting that business stakeholders use. This is a hands-on role on a small, fast-moving team. You'll have real problems end-to-end: from understanding a messy source system, to modeling it in dbt , to shipping dashboards and AI connectors and explaining the numbers to the people who depend on them.
Essential Duties and Responsibilities
- Design, build, and maintain data models in dbt that serve as trusted sources of truth for the business.
- Write clearly, optimized, well-tested SQL , this is the core of the job.
- Develop a deep understanding of our data sources (property management, accounting, and operational systems) and become a go-to expert on their nuances.
- Build dashboards and reports for business stakeholders and partners with them to turn vague questions into concrete, data-backed answers.
- Write and run Python scripts to automate workflows, move data, and eliminate manual processes.
- Follow modern development practices: version control with Git/GitHub , code review, CI/CD , documentation, and data quality testing.
- Proactively monitor and improve data quality catch issues before the business does.
Requirements
Qualifications
Must have
- Deep expertise in SQL : complex transformations, window functions, performance tuning, and a strong instinct for data modeling.
- Comfort with Python for scripting and automation writing, running, and debugging your own tools.
- Fluency with Git , GitHub , CI/CD , and modern development workflows (branches, pull requests, code review).
- Experience building dashboards and reports for business stakeholders ( Power BI , Tableau , Looker , or similar) and communicating insights clearly.
- Strong written and spoken English ; comfortable working async with a US-based team.
Strongly preferred
- Experience with dbt and the modern data stack ( Databricks , Snowflake , or similar cloud warehouse; Fivetran ; orchestration tools like Airflow or Dagster ).
- Experience in finance or real estate is comfortable with financial statements, terms, and metrics.
Bonus points
- Hands-on experience with Yardi data or other real estate platform data (major brownie points for this one).
Working Requirements
- Fully remote
- Fluent in English
- Will work 8:00 AM to 5:00 PM US Pacific Time (PST)
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