Senior Analytics Engineer — Remote Data Architecture Lead

Pets Best Insurance Services LLC

United States

A distancia

USD 113.000 - 169.000

Jornada completa

Hace 8 días

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Ventajas ofrecidas por este puesto de trabajo

Healthcare
Parental leave
Wellness Day
Retirement plan
Paid time off

Descripción de la vacante

Clarus is seeking an experienced Analytics Engineer to lead analytics engineering, own the data models, and optimize pipelines across dbt, SQL, Python, and Databricks. You will translate complex requirements into scalable data products and partner with engineering and business teams to deliver trusted analytics assets.

The role is remote in the United States, with a strong emphasis on governance, testing, and CI/CD practices to ensure data quality and reliability at scale.

Formación

  • Bachelor’s degree in a related field or equivalent professional experience.
  • 8+ years in data analytics/engineering with ownership of production models.
  • Proven SQL mastery and experience with dbt and Databricks.

Responsabilidades

  • Own analytics engineering roadmap and standards.
  • Design analytics architecture across bronze/silver/gold layers.
  • Develop dbt models transforming source data into analytics datasets.
  • Optimize SQL and use Python for data transformation and automation.
  • Create and govern data models for dashboards and data products.

Conocimientos

Advanced SQL
dbt
Python
Databricks
Data Modeling
ETL/ELT
Cloud Data Warehouse
Git & CI/CD

Educación

Bachelor's degree in CS or related

Herramientas

Databricks
Git
CI/CD

Descripción del empleo

Clarus is seeking an experienced Analytics Engineer to lead analytics engineering, own the data models, and optimize pipelines across dbt, SQL, Python, and Databricks. You will translate complex requirements into scalable data products and partner with engineering and business teams to deliver trusted analytics assets.

The role is remote in the United States, with a strong emphasis on governance, testing, and CI/CD practices to ensure data quality and reliability at scale.

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