Analytics Engineer

EquipmentShare•Columbia, MO

16h•Remote

About The Position

EquipmentShare is hiring an Analytics Engineer to support its Corporate Headquarters in Columbia, Missouri. The position is fully remote and supports the company’s mission to transform the construction industry through technology. The Analytics Engineer develops and manages data pipelines using SQL and Python, transforms data according to business rules, and creates or updates data models in dbt. The role translates business needs into technical specifications and timelines, tests and deploys changes, and monitors and improves data pipelines and ETLs. It also supports day-to-day reporting and analytics by reducing the complexity of accessing and querying cross-functional data. The role calls for someone adaptable, self-directed, detail-oriented, and effective at communicating with and influencing cross-functional stakeholders in a fast-paced environment. A high school diploma or equivalent education or experience is required. Employment is contingent on passing a background check; some roles also require a drug test depending on job responsibilities.

Requirements

At least 5 years of SQL experience creating complex SQL solutions to business problems.
At least 2 years of Python experience creating scalable processes to solve business problems.
At least 2 years of data modeling experience.
Experience modeling using dbt.
Experience working with git.
High school diploma or equivalent education or experience.
Strong verbal and written communication skills, including the ability to influence and manage cross-functional stakeholders.
Ability to work without constant supervision and be self-starting.
Ability to work quickly and think logically, especially under pressure.
Adaptability when priorities, timelines, or project scope change; attention to detail and ability to reprioritize.
Ability to handle problems with diplomacy and tact.

Nice To Haves

Experience using Looker Business Intelligence Tool.

Responsibilities

Develop and manage data pipelines using SQL and Python to extract data from various sources and transform it according to business rules.
Create and update data models in dbt to provide scalable, robust data solutions.
Translate business needs into technical specifications and establish job-completion timelines.
Create, test, and deploy changes.
Monitor and improve data pipelines and ETLs, proactively identifying potential issues.
Support day-to-day reporting and analytics by reducing complexity in accessing and querying cross-functional data.