Analytics Engineer

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Bridge33 Capital

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2012

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Bridge33 Capital is a commercial real estate investment firm that emphasizes a flexible and agile approach to identifying and capitalizing on unique investment opportunities. The company is driven by a relentless commitment to creating value for its investors, embracing an entrepreneurial spirit, disciplined acquisition, and intensive property management. Bridge33 Capital aims to be a leading real estate investment company by fostering a culture of innovation and excellence.

📋 Description

• 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

• 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. • 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. • Hands-on experience with Yardi data or other real estate platform data (major brownie points for this one).