Analytics Engineer

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

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)