At Salesloft, Customer Operations is pivotal to our company’s success. In this role, you’ll be a key member of our fast-growing and high-performing Revenue & Customer Operations Team. You’ll play a crucial role in driving customer retention and operational efficiency through data analysis and insights supporting teams like, including Customer Success and Professional Services.

On a day-to-day basis, you will be responsible for crucial operations within the Customer and Revenue organizations. Specifically you will:

  • Data Analysis: Conduct in-depth analysis of revenue and customer data to identify trends, patterns, and anomalies that impact revenue performance and customer outcomes. Utilize advanced analytical techniques to extract actionable insights from large datasets.
  • Querying Large Datasets: Develop and execute complex SQL queries to extract, manipulate, and analyze large datasets from multiple sources.
  • Ad-Hoc Analysis and Reporting: Fulfill ad-hoc data analysis requests from stakeholders to support decision-making and solve business challenges. Prepare and present findings in a clear and concise manner to both technical and non-technical audiences.
  • Cross-Functional Collaboration: Partner closely with our customer-facing teams like Customer Success, Customer Education, and Professional Services to deeply understand their business processes, and identify opportunities for data and insights to inform their work.


We are seeking a results-oriented, motivated and strategic data professional who can collaborate cross-functionally while remaining laser-focused on impacting our revenue numbers and customer outcomes. You will play a pivotal role in helping us scale in this next phase of rapid growth as a revenue organization.

If you’re looking for an opportunity to learn more, do more, and become more, then becoming a member of Salesloft’s Customer Operations team is the career path for you!


The team consists of operations, business, and data analysts with a drive to enable Salesloft to make better decisions. Our team shares a few common traits: they are accountable, unafraid to experiment, and continuously learning.


  • 4+ years experience in a data analysis or business intelligence role, preferably within a revenue operations or customer-facing team environment.
  • Proficiency in SQL for data querying and manipulation. Experience with data visualization tools such as Tableau, Power BI, or Looker. (Experience with Looker, LookML modeling, and in-depth knowledge of merge queries and filtering a plus.)
  • Strong analytical and problem-solving skills with the ability to translate complex data into actionable insights.
  • Excellent communication and collaboration skills with the ability to work effectively across teams and influence decision-making.
  • Snowflake, Github, and Jira experience a plus.


  • Attend Salesloft’s New Hire Orientation, where you will learn our Salesloft story and understand what makes our “Lofters” unique
  • Set your OKRs (Objectives and Key Results) with your manager and develop an action plan to achieve them
  • Begin 1:1s with your manager understand your 30-60-90 plan; shadow current members of the Revenue Operations team
  • Meet key partners in Strategy & Operations, Data & Analytics, Customer Experience, Finance, etc. – they will be key relationships for you
  • Become familiar with our CRM and data tech stack through training, self-study, and shadowing
  • Begin handling ad hoc reporting requests


  • Learn our CRM, Looker, and Snowflake data architecture, and how reports are pulled through self-study and shadowing.
  • Collaborate with Customer teams and Rev Ops to prioritize data and analysis needs,
  • Monitor key performance indicators (KPIs) related to customer retention, product usage, and customer organization effectiveness. Create dashboards and reports to track performance against targets and provide regular updates to stakeholders.


  • Lead data projects like investigating customer behavior through data analysis to uncover insights related to purchasing patterns, product usage, churn, and customer lifetime value. Use findings to inform customer success strategies aimed at maximizing customer retention.
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