Your First Analytics Engineering Job Should be in Consulting
3 min readOct 24, 2021

Hiring managers are looking foremost for proof of basic Analytics Engineering skills in candidates applying for their first Data Scientist job. A portfolio with a data cleaning project and a data storytelling project will get you hired quicker than only machine learning or competition projects.‍

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Don’t get me wrong, is great. But put yourself in the shoes of the hiring manager. Competitions do not show you can set up an environment or that you can handle any other file format besides a CSV of cleaned data. Do one or two competitions. Then focus on getting projects that are as close to the daily tasks of an analytics engineer as possible. I say this because your primary goal is to have 2–3 projects on your resume that demonstrate that you can tackle a problem from start to finish. Completing a ‘full-stack’ data project will always impress me more than demonstrating one’s ability to apply a model. I will give my opinion on the single best place to get this experience, but first, let’s talk about what is needed for a good resume.‍


Hireability (or a good resume) comes down to proof of experience. I don’t need to see how you tried 10 overtrained models to handle this one training dataset. In fact, think about this in production. When would you ever expect to build a model that isn’t retrained or used beyond a single run? This single-run model development is more like a Proof-Of-Concept (POC) project than anything else, which is prone to creating overfitted models that would never survive on real data. Everywhere I look, everyone says data cleaning is the biggest part of data science, so I know I’m not overstating it here. Ask someone farther along in the industry than you: “What are the core Analytics Engineering skills I would need in my first 90 days at startup?”‍

Take the advice of experienced people and layout the skills you would need for a project. For example, if I were trying to land a job at a SAAS B2C company, I would know they are likely to have a set of needed skills.

  1. Pulling together onboarding and marketing data and building retention funnels
  2. Creating subscription or Life-Time-Value (LTV) analysis in cohort form
  3. Communicating requirements for landing page tracking and a/b testing
  4. Creating technical requirements from business stakeholders

When I look at a resume and see that someone is just starting out in the field, I do not consider this a red flag against them. I immediately look at their school projects, internships, or alternate learning opportunities to see if they would be a good fit. I will always suggest two projects for the candidate applying for their first analytics engineering job: a data cleaning project and a data storytelling project.


I’ve tried so many types of projects and presentations of project summaries on resumes over the years. My experience has taught me that the best experience can be found in consulting jobs. They are often already divided into that perfect, 1–6 weeks timeframe. Consulting projects seek to solve an actual business problem with an actual business mess (helps a lot when writing about it on a resume). Additionally, they are partially constrained by the fact that the project manager had to spend some time thinking about the definition and steps of the project.

My advice is to try to find 2 to 3 consulting projects/externships while looking and applying for jobs. As you finish up each individual stage of the project, stop to write down a little summary. Think about what skills a hiring manager would be looking for and craft a couple of sentences that show you understood the business problem and know how to technically address it. By the time you have a couple of these summaries, you will have a complete project section for your resume and your new job. Reach out to tell me how it goes at And if you want to join our freelancer network to get your first job, visit us at