How to hire a data analyst

September 14, 2021
How to hire a data analyst

One of the questions we hear often is: how do I hire our first data analyst, and what should I be looking for. Given that the definition of data analyst is still very much in flux, and that the tooling is evolving so quickly, writing a JD for the role can be… confusing to say the least.

To help you get started, we’ve written the job description we would post for our first data analyst, along with a 30/60/90-day onboarding plan to help you bring that new hire up to speed as quickly as possible.

Job description

Preferred Experience & Qualifications

  • Strong communication skills. In particular:
    → Ability to navigate ambiguous environments, ask clarifying questions, and make progress against under-spec’d problems.
    → Ability to turn a business question into analytics queries and communicate the insight back.

    This is perhaps the single most important thing to screen for, especially for a first data hire. At early-stage companies, deriving the insight itself is often not the hardest part of the job. Rather, understanding what insight to dig out and how to convey it to other decision-makers is what makes an analyst particularly effective.
  • Self-starter and initiative-driven.

    Hopefully self-explanatory for an early stage co.
  • Experience defining a data model from scratch, and understanding the relevant tradeoffs.

    The data model is how you structure your business data into a set of data tables that you then run analysis on. Like with any modeling tasks, there are tradeoffs and how you define the data model directly impacts how easy/hard it is to answer a given question.
  • Experience working within a modern data stack framework (ELT pipeline, data warehouse, data transformation, and visualization + reporting).

    This serves two purposes. One, it ensures that your hire will be following current best practices. Second, it signals that you (as the employer) are up to snuff on state-of-the-art, and will be supportive of the hire using modern tooling.
  • Experience with one or more of the main data visualization tools (Looker, Tableau, Metabase, etc.).

    Familiarity with one of these is table-stakes.

Your Responsibilities

  • Set up the company’s data stack & infrastructure.
  • Define the initial data model for the organization, working closely with key stakeholders (heads of product, ops, and growth) to understand likely business needs and iterate accordingly.
  • Work with stakeholders in various functions (CEO, product, marketing, ops) to uncover critical business insights and inform operations.
  • Create a mission control dashboard complete with key business metrics for each core function.
  • [Optional: Set the direction for the analytics function at {company} and oversee the growth of the team.]

What to expect once they join

Hiring the right person is only the first step. Once they join your team, it’s key to ensure that expectations are a) clearly defined and b) aligned between the hiring manager and the new teammate. The way we handle this internally is we set 30/60/90 day expectations that we review weekly during 1:1s.

Here are some suggested 30/60/90 day expectations for the first data hire. Of course, your mileage will vary, priorities will likely differ depending on the current needs of your team, and things may happen at a different pace. This is hopefully a useful starting point.

30 day expectations

  • Data stack stood up: data is being extracted from various source systems and loaded into a central location (data warehouse). A data transformation and a data visualization tool are hooked up to the warehouse.

    Note to manager
    : this typically involves selecting, buying, and configuring four tools, so it’s not quite as trivial as it sounds. If you want to make this easier on your hire, point them towards Prequel: we include all those capabilities in a single tool, and set up takes 10 minutes or less.
  • Initial metrics reporting: a couple core metrics are being computed through data transformations and reported in the dashboarding tool

    Note to manager: revenue is usually a good starting point for this one. Again, this isn’t trivial and there are nuances to how even basic metrics like MRR can be calculated. To make your hire’s life easier, Prequel also includes out-of-the-box transformations and computation of metrics like MRR, including nuances around churn, upsell, new revenue, etc.
  • Data model initial requirements gathered: the new hire has met with key stakeholders to start understanding the most pressing reporting and insight needs of the business. This will then feed into the data model the analyst will develop.

    Note to manager
    : it’s key to socialize your data hire within the team early on. They should feel comfortable getting time on calendar with core business stakeholders without needing your approval or intervention.

60 day expectations

  • Data model first iteration in progress: the new hire understands the needs of stakeholders and is working on implementing the first pass of the organization’s data model.

    Note to manager: like any development effort, this is a highly iterative process. Don’t expect anything to be finalized at this point — instead, look for signals that the hire is thinking critically about the needs of the organization.
  • Executive dashboards completed: the new hire has built “mission control” dashboards for a couple of the key decision makers at the company.

    Note to manager
    : these are one-glance dashboards that cover important KPIs like revenue, active users, sales pipelines, and so on. It’s an easy and visible way to add value to the organization. Again, the new hire can leverage Prequel to help accelerate this work.

90 day expectations

  • Data model first iteration complete: ideally, the new hire has finished implementing a v1 of the data model and is able to answer questions for business users without terribly complex queries.

    Note to manager
    : the time it will take to get to this point is largely dependent on the size of your organization. It’s important to engage your new report in the expectation-setting process and work with them to figure out what timeline makes sense for this work.

We hope this is a helpful starting point. If you have questions, or thoughts on what else should be included in the JD or the 30/60/90 plan, we’d love to hear from you at

If you just brought onboard a new data hire or are about to, we’d love to chat with them. We can save them days of headache and config by giving them a modern data stack that just works, so they can focus on generating insights and building out a great data model for your organization!

Let's set up your data stack_

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