How to Land Your First Job as a Data Analyst

Cody West
Cofounder @ The Query

Cody is a data analyst and analytics engineer with 9 years of experience. He currently works in tech on growth and marketing data analytics.

Table of contents

You did it! 🎉 🥳

You now have a portfolio with 7 portfolio projects, have your Google Data Analytics Certification, and are either Tableau or Power BI certified.

At this point, you have the skills to land your first Data Analyst job.

Take a moment to congratulate yourself for all the hard work you put in.

Next, it’s time to set your sights on landing your first job!

First, remember that interviewing and landing a job is a skill in itself and takes practice, consistency, and grit, just like learning data analytics.

It’s less technically challenging and much more emotionally challenging.

But rest assured, you have the skills for the jobs — your portfolio should give you confidence and proof that that’s true.

In the last chapter of this guide, I’ll give you the strategies and resources you need to land that first job.

Let’s go.

Step 1: Emotional Preparation

Let’s face it, interviewing is emotionally challenging.

You’re putting yourself out there and will inevitably have to face rejection.

Rejection sucks.

But it’s also part of the game you have to play.

Accept this as an inevitability and have a plan for dealing with it.

Here’s what I do if I’m dealing with rejection:

First, I take time to accept how I feel. I don’t try to suppress the negative feelings because I know that will just prolong them.

When I’m feeling a difficult emotion, I like to go on long drives in the car or long walks around the area I live.

Both of these activities give my brain time to ruminate on what happened.

Hard workouts (e.g. sports, weight lifting, running, etc.) are also great for physically working through difficult emotions.
When I’m ready, I will also talk to friends or family members I deeply trust about what happened and how I’m feeling.
“Talking it out” is a great way to process emotions.

I try to remember to be kind to myself and keep this phrase in mind: “This too shall pass.”

I may feel terrible now, but at some point, I won’t because feelings don’t last forever.

I also give myself a set amount of time to “feel bad”. Usually, it’s a day or two or three.

But once that period of time is up, I compose myself and continue moving forward.

When it’s that time, I reframe whatever happened as an opportunity for me to learn and grow.

Negative emotions are incredibly effective at helping you learn and grow — here’s why:

Say you do something that makes you feel guilty.

Guilt is a terrible emotion to experience and the negative feeling of guilt teaches you not to do whatever you did to make yourself feel guilty because you don’t want to have to feel guilt again.

In the context of interviewing, say you get rejected because you bombed the “tell me about yourself” interview question.

You blew it because you didn’t prepare enough, so to avoid feeling more rejection, you prepare much more for that question for your next interview.

Angela Duckworth wrote an amazing book called Grit.

I highly recommend reading it or at a minimum, going through this book summary.

Having grit means having courage and resolve.

Grit is important in landing your first data analyst job because it’s going to be difficult.

That’s a fact.

But if you approach interviewing as something you’re going to do and iterate on until you’re successful, you WILL land that first job.

Step 2: Preparing your resume

Your resume is only important for one thing: landing interviews.

There are two key points to remember when crafting a resume:

  • The audience for your resume is recruiters
  • Recruiters will spend less than 1 minute reviewing your resume
With those in mind, let’s go through some core principles in crafting a strong resume.

Avoid technical jargon

Remember, your resume is for recruiters.

Avoid too much technical jargon if there’s a way to say something in plain English.

For example, instead of saying “Built Streamlit app with Airtable API and GCP to analyze personal habits”, say “Built a personal habit tracker dashboard to improve productivity.”

The latter is much easier to understand.

Also, it’s best not to include a Skills section on your resume.

You want to SHOW you have the skills, not TELL.

Instead, mention the skills in the bullets for your work experience.

Using the personal habit tracker dashboard example above, one of the bullets could be:

  • Built a personal habit tracker dashboard to improve productivity using the following technology: Streamlit, the Airtable API, and GCP (pub/sub, cloud scheduler, and cloud functions).

Short, sweet, and no-fluff

You have less than 1-minute to impress a recruiter to land an interview.

You can’t afford to be verbose.

Try to say what you need to say using as few words as possible.

ChatGPT is excellent for this.

Prompt it with something like:

“Edit the following sentence or paragraph and make sure it’s as short and concise as possible without losing the underlying meaning.”

You may need to iterate a few times here, but if you do this for every sentence in your resume, you’ll dramatically improve it.

Remove irrelevance

Again, you only have 1-minute to impress.

You shouldn’t include anything irrelevant to your “angle”.

If you played soccer in High School and won your regional MVP, only include that if you’re applying for a sports-related Data Analyst position.

And even then, ideally, you’d tie that accomplishment to something data analytics-related like a portfolio project where you analyzed your High School soccer stats.

Include only highlights

Everything on your resume should be a highlight and be impressive — avoid anything neutral or negative (obviously).

You only have seconds to impress, so you don’t want the recruiter focusing on something that doesn’t make you sound awesome.

You should also ignore the conventional advice of ordering your resume chronologically.

Instead, order it based on impressiveness and relevance.

Place the most relevant and most impressive callouts on top.

Include impressive numbers and achievements

Achievements and outcomes should be the focus of your resume, not responsibilities.

What positive outcomes did your responsibilities lead to?

Use big and impressive numbers here if you can.

Recruiters love big and impressive numbers 🤓

Be professional, yet unique

You want to come off as professional, so make sure to:
  • Use a Gmail or custom domain (e.g. or — NOT @yahoo or @hotmail or any others).
  • Don’t include a photo.
  • Link your portfolio, LinkedIn, and GitHub (if you host your SQL code there).
  • Don’t include your address, just State and City
  • Always send a PDF, never a Word doc or anything else.
  • Name your resume “FirstName LastName Resume.pdf”
  • If you’re handing in a physical resume, use high-quality paper like this.

Uniqueness is memorable.

On my resume in the summary section, I say “I write SQL from my log cabin an hour from the nearest grocery store.”

So ask yourself, “What makes me unique?”

Once you’ve got some ideas, do the following:

  • Use bold to capture attention to important callouts
  • Link your portfolio projects in your work experience section
  • Include a summary section where you state something unique and memorable about yourself (e.g. “I live in a log cabin an hour from the nearest grocery store”).
  • Don’t be afraid of breaking conventional resume norms if it makes sense for who you are.

Tailor your resume to the job

There are lots of different types of data analysts:
  1. Roles (e.g. Financial Analyst, Marketing Analyst, BI Developer, etc.)
  2. Companies (e.g. Pepsi, Google, JP Morgan, GitHub, etc.)
  3. Industries (e.g. B2B Saas, agriculture, banking, etc.).

With these variances in job, company, and industry, one resume isn’t going to cut it.

You’re going to want multiple versions of your resume where you tweak your experience to better align with the role you’re applying for.

Start by creating one resume for the first job, company, and industry you want to apply for.

After you finish applying for that job and are working on your next application, slightly modify your resume to better align with that job’s requirements.

You can reuse your resume for similar roles at similar companies in similar industries.

To keep them organized, I recommend saving each new version and titling them: “FirstName LastName Resume (Role - Company - Industry)”.

Just remember to delete the (Role - Company - Industry) section before you apply.

99% of people don’t tailor their resume to the job because it’s time-consuming.

But trust me, it’s all about quality, not quantity when applying for jobs.

Taking an extra 10 minutes to optimize your resume is 100% worth it and will put you ahead of the people just spamming their resume to every job title with the word “analyst” in it.

Get resume feedback

There’s a subreddit called /r/resumes where you can post your resume and get feedback on it.

Once your resume is complete, post it there and ask for feedback.

Then implement the feedback.

Next, do the same but in the /r/dataanalysis subreddit.

Implement the feedback.

Others will see things you don’t which will help with incremental improvements and get you closer to landing that first job.

Step 3: Preparing Your Cover Letter

Many roles require you to submit a cover letter.

But most of the time they aren’t even read.

If you’re limited on time, spend about 90% of your time making sure your resume is amazing and 10% on your cover letter.

Even though it’s less important, your cover letter should at a minimum not hurt your chances of landing an interview.

There are two very good resources for learning how to craft a strong cover letter:

  1. Princeton’s Cover Letter Guide
  2. This post on Reddit
Here are also a few principles to keep in mind:
  • Keep it short and sweet — the cover letter in the Reddit post above is too long. Use the same formula for crafting the cover letter, but make it about ¼ of the length.
  • Match formality and communication style to the type of company and industry.
  • Tech = more informal
  • Banking = more formal
  • Make it about how you can help the company you’re applying for, not about yourself.
A cover letter is a necessary evil, so write a decent one, but don’t spend too much time worrying about it.

Step 4: Exhaust Your Network

The best way to land any job is by being referred.

If you took the advice at the beginning of this guide and used the 6 month learning period as a time to network, now is the time to use that network.

Share on LinkedIn that you finished your portfolio and that you’re looking for a data analyst role.

I do NOT recommend using the LinkedIn “#opentowork” insignia.

The best candidates don’t do this because they don’t need to.

Recruiters want to hire the best candidates so there’s a bias that can exist for recruiters when they see that #OpenToWork badge on a profile.

DM people you know letting them know you’re looking for a Data Analyst role and if they know anyone you should reach out to.

If they say they do, ask them for an introduction.

Do you have family members or friends you know personally that could introduce you to recruiters or data analytics hiring managers at companies they work at?

Go through and exhaust that list of people.

Using your network gives you the highest probability chance of getting your foot in the door for an interview, so be exhaustive during this process.

Step 5: Apply Online

After exhausting your network, it’s time to begin applying for jobs online.

First, make sure you’re tracking everything.

I like using a Google Sheet for this with the following columns:

  1. Company
  2. Job Title
  3. Application URL
  4. Applied Date
  5. Heard back?

You’ll most likely be applying to ~100 jobs and you’ll want to know where you applied and when you applied.

Make sure you’re tweaking your resume to match the job requirements as closely as possible.

Job Websites

Here are the job websites I’d recommend parsing through to find Data Analyst jobs:
Use those, but you may also need to expand and use websites like Indeed and Monster.

Data Analyst Job Titles

Don’t make the mistake of only searching job websites for “data analyst” jobs.

There are many different data analyst job titles you should be searching for:

  1. Financial Analyst / FP&A Analyst
  2. Marketing Analyst / Growth Analyst
  3. Risk Analyst
  4. Business Analyst
  5. BI Analyst / BI Engineer
  6. PowerBI Developer
  7. Product Analyst
  8. Marketplace Analyst
  9. Tableau Developer
  10. Medical / Health Care Analyst

The list above is not exhaustive so it’s worth doing your own research into what roles analyze data in the industries and companies you’re looking to work at.


Applying for jobs online has a very low success rate.

Expect to hear back from less than 5% of the job applications you submit.

This is normal and says nothing about who you are or your abilities.

Don’t take it personally.

Treat applying to jobs like a full-time job and shoot for a minimum of 5 new job applications submitted per day.

The interview process will take ~2 months on average to land a full-time position, so you can apply to 100s of companies in this time.

Ideally, you have options that give you negotiating leverage, so again, treat this like a full-time job and be consistent about it.

Step 6: Cold Outreach

When you’re applying for jobs the traditional way (i.e. applying through applications forms online), you end up having to compete with 1000s of others which is why the success rate is so low.

Wouldn’t it be better if you had a way to stand out and increase your success rate?

Cold email outreach is how you do that.

After applying online (NOT before), email recruiters and hiring managers to increase the probability they give your resume a fair look.

Here’s how to cold email recruiters and hiring managers:

1. Create a tracking template

You’re going to be sending a LOT of emails, so you need a spreadsheet to track it all.

Here are the columns I recommend creating:

  1. Name
  2. Email
  3. Company
  4. Job application link
  5. First email send date
  6. Follow-up email #1 send date — make this a formula that adds 3 days to the email send date
  7. Follow-up email #2 send date — make this a formula that adds 7 days to the email send date
  8. Responded by date

2. Who to email?

In most cases, email the recruiter.

They’re the gatekeepers.

Your first interview will be with a recruiter too.

Depending on the size of the company, the recruiter you should email varies, but an approach you can use for most companies:

First, go to the company's LinkedIn company page and click on People:

Next, search for “recruiter” or “talent”:

Look for the person with the most relevant title (e.g. Data Recruiter, Technical Recruiter, etc.).

If there are no recruiters (because it’s a startup with only a few dozen people), try to find whoever is hiring for the role (Head of Analytics, etc.).

In some cases, it might even be the founders.

3. Find their email

There are countless tools nowadays that help you find email addresses.

Here are a few to try:

If you need help using these tools to find email addresses, just go to YouTube and search “[ToolName] find email address guide.”

If you can’t find their email, you can try a LinkedIn or Twitter DM, but these won’t work as well so do your best to find their email.

4. Send an outreach email

Outreach emails should be:
  • Personalized to the person and company you applied for
  • Short, sweet, and to the point (no more than ~5-6 sentences
  • Mention the #1 thing that makes you an awesome fit for the role they want to hire
  • Try to personally relate to the role or company
  • Ask for an interview directly
  • Write a compelling subject line
Here are some resources you can check out to learn about crafting compelling cold outreach emails:

5. Follow up twice

Follow up 2-3 days after your first email.

Follow up 5-7 days after your second email.

Reply to your original email with a sentence or two reminding the person that you’re interested in speaking with them about a role for their company.

Keep these follow-ups short. No more than 2 sentences.

6. No response?

If you don’t get a response after the 2 follow-ups, find the next most relevant person at the company you applied for and start this entire process over again.

Persistence wins in the long run.

Step 7: Preparing for Interviews

Many people just “wing it” when they interview.

HUGE mistake.

Interviewing well is all about preparation.

There are two VERY important reasons to prepare for interviews:

  • Preparation improves your confidence so you bring the best version of yourself to the interview.
  • When you’re prepared, you’re more likely to engage in “active listening” versus trying to decide what you’re going to say next. This leads to better, more thoughtful responses on your part.

General advice

When you have an upcoming interview, treat preparing like a full-time job.

Use every free minute you have to prepare.

I’ll cover how to prepare for each specific type of interview below, but here are some tips for preparing more generally:

  • Read the entire job posting at least 5 times. Try to understand both “why they are hiring the role” and “what you’d need to do to be successful in the role.
  • Research the company and be able to talk about 1) their mission, 2) their culture, and 3) their business model (i.e. what products/services do they provide and how do they make money?).
  • If there are topics in the job posting you aren’t familiar with, become familiar. For example, if it’s a Marketing Analyst role that mentions SKAN and you don’t know what that is, research it and learn about it. You don’t need to be an expert, but you should at least know what it is.

Remember, interviewing is a skill, and the more you do it, the better you’ll get at it.

Expect to be nervous.

That’s normal.

Nerves can help you in an interview setting because they activate certain biological systems that improve performance.

But you can also have too much of a good thing.

Make sure you’re doing everything you can to control your nerves like:

  • Minimizing caffeine consumption so you avoid the jitters.
  • Getting lots of sleep the night before — do NOT pull an all-nighter to study for an interview.
  • Work out the morning of your interview.
  • Go on a walk before your interview to clear your mind.
  • Right before you walk in (or login) to an interview, take 8 conscious, slow deep breaths to center yourself.
  • Do anything else that helps calm you down and keeps you present and in the moment.

I also recommend reading this guide on preparing for data analytics interviews and reading the book Kock ‘em Dead Job Interview: How to Turn Job Interviews into Paychecks.

Step 8: The Recruiter Screen

The recruiter screen is typically the first interview you have and is over the phone most of the time.

It’ll be 30-45 minutes and the recruiter is trying to assess one thing: Does this person meet the requirements for the job?

The good news for you is that those requirements are listed on every single job posting.

Here’s how to prepare for the recruiter screen:

Pull up the job posting and look at the job requirements section:

Also, look at the responsibilities section:

See how the 2nd bullet in the “What You’ll Do” section mentions marketing attribution?

This is a Marketing Data Analyst position, so it’d pay to have a portfolio project related to Marketing that you can talk about when interviewing.

If not, come up with something as relevant as possible to “marketing attribution.”

Now prepare a story that shows you’re previous experience and that who you are as a person matches that requirement.

When preparing a story, most recruiters and companies prefer you tell the story using the STAR format.

Here’s a guide on using the STAR method.

I recommend preparing 3-5 stories relevant to the bullets above.

For each story, write short bullets for the order in which you’d like to tell the story in.

Then practice telling each story using this structure:

  • Tell the story 3 times using the bullets as guardrails
  • Tell the story 3 times without using your bullets
  • Go to sleep (the story will solidify in your mind)
  • Tell the story at least 1 more time before the interview
You should also prepare answers to the following questions:
If you do all the above, chances are you’ll nail the recruiter screen, which is typically the easiest interview.

Step 9: The Technical Interview

If the role has a technical interview (some entry-level roles don’t), it will be one of two things:
  1. A take-home analysis Case Study
  2. A live SQL / Excel interview
If you have a takehome, check out these resources to prepare:
If you have a live SQL interview, check out these resources to prepare:
I also HIGHLY recommend using both of the resources below — leading up to the interview, shoot for completing 10 - 30 SQL practice problems:

Step 10: The Behavioral Interviews

You’ll probably have 3-6 behavioral interviews depending on the type of company you’re interviewing at.

An interviewer is looking for a few things from you in a behavioral interview — soft skills, role fit, and culture fit.

Soft Skills

Here are the soft skills most interviewers will be looking for:
  • Communication skills and storytelling
  • Critical thinking and problem-solving abilities
  • Business acumen and understanding of relevant industries
  • Attention to detail
  • Teamwork and collaboration

You should also review the job posting and look for any other soft skills mentioned in the requirements section.

Now, prepare ~3 stories you can reference that SHOW you have these skills.

Here are some of the most common behavioral interview questions to prepare for:

  • Tell me about a time you had a disagreement. How did you handle it?
  • Tell me about a time you had a setback. How did you handle it?
  • Tell me about a time you had to deal with a difficult co-worker. How did you handle it?
  • What’s your great strength and weakness?

Role Fit

Every data analyst role requires something a little different depending on the company you’d work for, the people you’d work with, and the day-to-day requirements of the role.

When it comes to the role, most job postings do a decent job of explaining the type of person that the hiring manager thinks will excel in the role.

When you’re preparing for role-related interview questions, always start with the job posting itself because it’ll tell you exactly what to prepare for.

Here’s the responsibilities section of an example job posting:

We can see they want someone that:
  • Knows a bit about Marketing Analytics
  • Understands what attribution is and the nuances there
  • Understands how to perform customer analysis

Come up with stories for each bullet (sometimes one story can cover multiple bullets).

This is the perfect opportunity to talk about your portfolio projects.

For example, say you did a customer behavior portfolio project and you’re applying to the job above. Make sure you craft a story about that project that you can use to answer any customer or audience analysis-related question you’re asked.

You also want to make sure you display to the hiring team that you’re energized and excited about the role itself.

A paycheck can’t be the only motivation for you, so really think about what piques your curiosity about the role and why you’d enjoy it.

Culture Fit

Most companies nowadays will NOT allow their hiring managers to say if someone is a “culture fit” or not because it can be seen as biased and discriminatory.

But that doesn’t change the fact that people want to work with other people they like.

To be “liked,” the only book you need to read on the subject is How to Win Friends and Influence People (I know, I’m getting repetitive).

But you should also:

  • Read/watch any info available on the company's culture.
  • Prepare stories about why you relate to the mission and culture of the company and what’s motivating about it to you.
  • Prepare stories that highlight the best part about what makes you, you.

Step 11: Iterate and Improve Until You Succeed

While you’re interviewing, pay attention to any feedback you get on how to improve.

When you get rejected, ask for feedback!

Maybe your portfolio needs to be cleaned up or simplified.

Maybe you need to work on telling better stories that show your skill.

Maybe your resume isn’t landing recruiter screening interviews.

Whatever it is, make sure you’re taking the feedback and immediately applying it.

Maybe you’re not getting direct feedback, but things are not moving in the direction you want them to.

Use that time to continuously improve.

Improve your resume and portfolio.

Continue creating new data analysis projects and adding them to your portfolio.

Stay active on LinkedIn, participating in the community.

Continue taking action to improve yourself as a data analyst.

‍At some point, it WILL work out.

But be careful — the definition of insanity is doing the same thing over and over, but expecting a different result.

I see a lot of people who don’t iterate or change anything when they aren’t getting interviews or landing a position.

They just keep submitting more applications. Or they continue showing up to interviews without preparing.

Don’t be one of these people.

Keep improving, stay optimistic, and be patient.

If you do all these things, I’m confident it will work out for you eventually.


You only have to land one data analyst job to get your foot in the door.

After your first job, the next will get significantly easier because you have real-world experience.

I hope this guide was helpful for you, I put a lot of time and energy into it.

But just like interviewing requires interaction and continuous improvement, so does teaching and writing.

If you have any questions about this guide or feedback for me, hit me up on LinkedIn or at The Query on Twitter 🤓
And to stay up to date on what I’m working on, sign up for my newsletter here.

Good luck my friend!

Cody West
Cofounder @ The Query

Cody has worked in data for 9 years as a data analyst and analytics engineer focusing mainly on growth and marketing analytics.

He has a wide breadth of experience ranging from working on a 40 person analytics team to being the first analyst at a startup to build the analytics function.

He’s also a data entrepreneur and has built and sold 2 companies in the marketing data space. Currently, he works in tech on growth analytics and GTM strategy.

Cody lives in a log cabin in the woods an hour from the nearest grocery store thanks to Space X’s Starlink internet.