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Senior Analytics Engineer

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Salary

$160,000-$165,000

Location

Remote

The Senior Analytics Engineer is responsible for designing, building, and optimizing the analytics infrastructure. This role partners with stakeholders across the business to model clean and reliable data sources, enable self-serve insights, and drive decision-making. It bridges analytics and engineering, with full ownership of data workflows from ingestion to insight. The Senior Analytics Engineer works closely with the Head of Data on strategic initiatives and plays a key role in shaping the direction of the modern data stack as the organization scales.

What you'll do

  • Own the development and maintenance of dbt models in our Snowflake data warehouse
  • Define and implement data modeling standards, ensuring trusted and well-documented datasets
  • Collaborate cross-functionally with business, product, and ops teams to deliver insights
  • Enhance ELT pipelines using Fivetran, dbt, and Git workflows
  • Improve pipeline reliability and performance in partnership with data engineering
  • Build dashboards and reporting tools using Looker, Sigma, or Tableau
  • Define and maintain key metrics, supporting self-serve analytics across teams
  • Lead data quality and governance initiatives
  • Contribute to architectural decisions and mentor junior analytics team members

What we're looking for

  • 6+ years of experience in analytics engineering, BI, or data engineering.
  • Strong SQL skills and deep experience with data modeling.
  • Hands-on experience with dbt and the modern data stack (Snowflake, Fivetran, Looker/Tableau, Git).
  • Working knowledge of Python and data engineering workflows.
  • Excellent communication, stakeholder management, and relationship-building skills to effectively partner with leaders across multiple functions.
  • PC skills including working knowledge of the Microsoft environment and the ability to access, manipulate, organize and relay information in a meaningful way.
  • Ability to work in a high-growth, dynamic environment.
  • Familiarity with cloud infrastructure (AWS/GCP), orchestration tools (Airflow) preferred
  • Experience in real estate, mortgage, or financial services is a plus
  • Experience with Airflow for orchestrating and scheduling data pipelines, and Python-based ETL/ELT workflows for data engineering preferred

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