Analytics Engineer
- Role
- Data Engineering
- Employment
- Contract
Open to PH only. Set where you work from to check your eligibility.
No BS summary
Analytics engineer hired out of Manila who lives in SQL — the core of the job is writing clean, well-tested SQL and modeling messy property-management and financial source systems into trusted datasets in dbt, then shipping dashboards and explaining the numbers. Must-have: deep SQL, Python comfort, Git/GitHub/CI-CD workflow, dashboard experience, and strong English. Fully remote but you work 8:00 AM–5:00 PM US Pacific Time alongside a US-based team.
Core skills
Required skills
Optional skills
Required languages
POSITION SUMMARY: 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-of-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. Analytics Engineer (Offshore / Remote) 1 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)
What you'll do
- 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 partner 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 and catch issues before the business does.
What they require
- 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).
- Strongly preferred: experience in finance or real estate — comfortable with financial statements, terms, and metrics.
- Bonus: hands-on experience with Yardi data or other real estate platform data.