EquipmentShare is Hiring an Analytics Engineer.

EquipmentShare is searching for an Analytics Engineer. You will serve as the point person for transforming EquipmentShare's fleet operations and supply chain business and analytics needs into a scalable and repeatable structure. You will partner with Operations and Finance stakeholders and the Fleet Operations team to create and monitor data pipelines, with a focus on developing processes and architecture efficiently and for the first time. Our ideal candidate sits at the intersection of Analytics and Data Science.

Primary Responsibilities

  • Build and maintain data models quickly, refining over time to get production models
  • Reduce tribal complexity of querying data
  • Develop pipelines and testing automation to ensure data quality and integrity
  • Strong owner in developing business-centric data models with minimal guidance and 
    comfort deriving answers from ambiguity
  • Codify business rules into data models/testing
  • Develop  and  manage  data  pipelines using  SQL and Python that  extract  data  from 
    various sources and transform it according to business rules
  • Straddle the data architecture and operations worlds, choosing the right tool at the right 
    time to make the right decision for the business
  • Convert business needs into technical specifications and establish a timetable for job 
    completion
  • Create, test, and deploy changes
  • Continuously monitor, improve, and proactively identify potential issues to improve the 
    data pipelines and ETLs

Why We’re a Better Place to Work

  • Competitive compensation packages 
  • 401 (k) and company match
  • Health insurance and medical coverage benefits
  • Unlimited paid time off
  • Generous paid parental leave
  • Volunteering and local charity initiatives that help you nurture and grow the communities you call home
  • Stocked breakroom and full kitchen (corporate HQ)
  • State of the art onsite gym (corporate HQ)/Gym stipend for remote employees
  • Opportunities for career and professional development with conferences, events, seminars, continued education

About You 

The opportunity for career growth is unparalleled at EquipmentShare, where you’ll find no
shortage of challenging yet fulfilling work, chances to build new skills and supportive teammates
who will push you to achieve your best.
Our mission to change an entire industry is not easily achieved, so we only hire people who are
inspired by the goal and up for the challenge. In turn, our employees have every opportunity to
grow with us, achieve personal and professional success and enjoy making a tangible
difference in an industry that’s long been resistant to change.
If you’re an analytics engineer with a deep passion for data, EquipmentShare could be the
perfect place for you. With a fast-paced, fast-growing company environment, the opportunity for
professional growth and development is unparalleled. At EquipmentShare we have a strong
belief and support in supporting the business with data; as a result, processes and models you
build will drive real impact on analytics across the company.

Skills & Qualifications 

Minimum Qualifications: 

  • 3+ years of SQL experience, creating complex SQL solutions to business problems
  • 1+ years of Python experience, creating scalable processes to solve business problems
  • 2+ years of experience data modeling
  • Experience working with git
  • Experience working in the AWS landscape with AWS products
  • Desire to thrive in a high-paced environment
  • Strong ability to adapt and be flexible within the scope of a given project as vision, 
    priorities, and timelines shift

Preferred Qualifications:

  • Experience working operational and supply chain data sets and techniques. 

EquipmentShare is committed to a diverse and inclusive workplace. EquipmentShare is an equal opportunity
employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation,
protected veteran status, disability, age, or other legally protected status.

 

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