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Expert Tips to Perfect Your Data Engineer Resume​

According to the US Bureau of Labor Statistics (BLS), the median salary for data engineers is $94,000. At the same time, the expected annual growth rate is nine percent year over year (faster than average).

It’s no wonder software engineers are flocking toward data engineering roles, but data engineers require a rare combination of skills to succeed.

They need to be great developers and have an appreciation for how other members of their team use data. While data scientists need data that can be plugged into their predictive models, data analysts need a queryable database to create visualizations for executives.

It’s not easy to demonstrate in a single-page resume that you can build robust data pipelines, create ETLs for different data sources, and ensure uptime of all data congestion. How can you ensure you cover all your bases in your data engineer resume?

While there are no hard and fast rules, we’ve talked to hiring managers at top tech companies to distill what works and what doesn’t to help ensure you get that first-round interview. In short, here’s what you need to do:

  1. First and foremost, you should include the right skills in your resume skills section. Companies use automated software to weed out applicants at this stage, so use specific keywords in your skills section to get past these filters.
  2. Make sure your resume is in the right format. You have to not only get past the automated filters but also make your resume appealing to the hiring manager.
  3. Quantify the impact of your work experience. Numbers speak louder than words, so use quantitative metrics to shout about your qualifications for the role to which you’re applying.
  4. Tailor your resume to each role to which you’re applying. It does take a bit of time, but you will land significantly more interviews by customizing your resume to each data engineer job description.

The data engineer resume skills section​

Believe it or not, the “skills” section of your resume is one of the most important. Why? Before a human reviews your resume, an automated filter scans it, and you need to appease the automation wizard.

Companies use an Applicant Tracking System (ATS) to manage all applicants they get for a given role. In addition to helping companies manage applicants, an ATS allows the hiring manager to filter out candidates based on certain keywords.

So first things first, you need to get past this filter before a person ever even considers your qualifications for the job to which you’re applying.

You need only to include the hard skills that qualify you for the given data engineering role. Exclude soft skills. For example, saying you have “strong communication skills” is meaningless without context.

For data engineers explicitly, there are more existing technical skills than you could ever have. For this reason, companies only use ATS filters to screen for hard resume skills. Here are some common ones you can list to get past the keyword filters.

Sample data engineer skills to include on your resume

Programming languages: Python, Scala, Java
Data processing: Spark
SQL: Redshift, Postgres, MySQL
NoSQL: MongoDB, Cassandra, ElasticSearch
Storage: Parquet, Avro, Arrow, JSON
Orchestration tools: Airflow, Luigi, Azkaban
Cloud providers: AWS, Azure, GCS
AWS tools: EMR, Lambda, S3, Athena, Glue, RDS

You would never be expected to have all of these. Instead, you should demonstrate a mastery of a few tools and languages instead of a light breadth of a whole host. Having a laundry list of skills is a big red flag to the hiring manager who will review your data engineer resume.

As a rule of thumb, only include skills for which you'd be comfortable being interviewed. A surefire way to get on an employer's blacklist is if you lie on your resume. Don’t do it; it’s just not worth it. You would be much happier landing a data engineering job that you’re a good fit for than having to scramble on day one.

Format your resume correctly​

Ensure the format of your data engineer resume format is appealing to the employer and consumable by the automated filters. To that end, here are some quick resume formatting tips:

  • Keep your resume to one page.
  • Don’t put your full address. Just your city and zip code.
  • Avoid any graphics, images, or charts on your resume. The ATS can’t read these.
  • Triple and quadruple-check for grammar and spelling errors. Don’t let this be the reason you're skipped over for an interview.
  • Only include a resume objective if you have a particular passion for the job you’re applying to or undergoing a career change. Otherwise, leave it out.
  • If you’re fresh out of college looking for your first full-time data engineering role, include relevant classes you took.
  • Every bullet on your work experience should be a complete thought. Avoid big blocks of text.
  • You should have one simple goal as your north star with your resume format: make the reader's job as simple as possible.

Put yourself in the shoes of the person reviewing hundreds of resumes for a given role. You don’t want to read walls of text spanning multiple pages. You want to read something concise that conveys why the applicant is a good fit.

Education for senior vs. entry-level data engineers​

When you’re a data engineer with a few years of experience under your belt, your education matters less than your work experience.

For that reason, the education section of your resume will vary if you’re an experienced data engineer vs. fresh-out-of-college or boot camp.

Education section differences

Entry-level data engineer:

  • Include relevant software engineer, statistics, or math classes you studied in school
  • Include your GPA if it was greater than 3.2

Experienced data engineer:

  • No need to include college classes on your resume; use this space to talk about your experience
  • No need to include your GPA
  • Don’t waste space with classes you took in school. Since your goal should be to keep your resume to one page, optimize that space as a senior data engineer. Similarly, your GPA won’t make a convincing case of your qualifications once you have a few years of work under your belt.

As an entry-level data engineer, you need to demonstrate your capacity for learning new technical skills. What better way than talking about the tough classes you studied?

Resume objective for data engineers​

Most data engineers should not include a resume objective on their resume. Why? It comes back to the aim of making your resume one page.

Most resume objectives only mention generic information that can otherwise be gleaned by reviewing the rest of your resume.

As a rule of thumb, if you’re using the same resume objective for multiple job applications, just exclude it.

There are two instances in which it’s worth it to include a resume objective.

  1. If you have a particular interest in the role or company to which you’re applying
  2. You’re undergoing a career change
tip

WRONG — generic resume objective

Looking for a data engineering role where I can leverage my Python knowledge to turn disparate data sources into actionable insights for a data-driven organization.

RIGHT — resume objective that conveys passion for the company's mission

Data engineer seeking to leverage my experience in building data pipelines to contribute to the Stripe mission of making payments easy and accessible for small businesses across the world.

RIGHT—resume objective for a career change

Data engineer transitioning from a career in software engineering looking to work with Apple to leverage my experience with ETLs to create products that make it easier for non-coders to build businesses.

Quantify the impact of your work​

You’re a data engineer, so using numbers is the best way to talk about your work experience. Data engineers are unique because you know exactly how much raw data you’re consuming and how much clean, polished data you’re pushing out to your data warehouses.

You need to convince the hiring manager that you’re the best fit for the data engineering role to which you’re applying. To make your data engineer resume better than 95 percent of others, quantify the impact of your work.

How to quantify your work as a data engineer

  • Magnitude of data with which you worked. Example: Built a data pipeline that ingested 3 billion rows of data daily from 17 different data sources and piped that data into Azure
  • Cost savings. Example: Built a more efficient ETL using Airflow and Redshift that saved the company $320,000 annually
  • Revenue lift. Example: Created consistent data sources that were used by the data science team to create marketing mix models, resulting in $1.2M in annual revenue
  • Uptime. Example: Created monitoring alerts for data pipelines that improved the uptime of the network by 17% year over year
  • Speed improvements. Example: Used Spark Streaming to consolidate and clean transactional and event data, resulting in speed improvements of 24% in the production web app

Numbers are more convincing than vague accomplishment statements. Whenever you can (even if they’re estimates), try to quantify the impact of the work you did in previous roles.

No matter where the hiring manager looks on your resume, they should come away feeling that you deserve a phone interview. The best way to make such a convincing case is to let the numbers speak on your behalf.

Just to hammer home the point one more time, consider which work experience is more convincing:

WRONG—vague work experience

_AT&T_
April 2015 - January 2018, New York NY
Data Engineer
Automated ETL processes to streamline data workflows
Created data pipeline that ingested streaming and transactional data and output cleaned data to Redshift

RIGHT—quantify the impact of your work

_AT&T_
April 2015 - January 2018, New York NY
Data Engineer
Automated ETL processes across billions of rows of data which reduced manual workload by a monthly 33% 
Maintained data pipeline up-time of 99.9% while ingesting streaming and transactional data across 7 primary data sources using Spark, Redshift, S3, and Python

Entry-level data engineer resume projects​

If you’re an entry-level data engineer without any work experience (or “fresher,” as the kids call it these days), you need to convince the hiring manager that you’re worth interviewing.

Employers love to see candidates going above and beyond by highlighting personal projects they’ve worked on related to their careers. How can you do that? By talking about past projects on which you’ve worked.

For an entry-level data engineer, anything counts! As long as you were ingesting data and making it usable for another party, it’s worth including it on your resume.

If you have no such projects, now would be a great time to work on one. Here are some project ideas you can include:

Sample projects for entry-level data engineers

  • Created web scraper in Python for fantasy football and developed a data pipeline to output that data into a MySQL database
  • Created a stored procedure in the database for the D&D club to monitor the performance of all players over time
  • Volunteered with a local flower delivery company to automate the ingestion of their vendor data, saving 25 hours of manual work each month
  • Worked with the university theater company to create a database of all patrons who came to paid shows over the last 5 years
  • Used the Rottentomatoes API to create a robust time-series database of all movie scenes since 2015

It doesn’t matter if the project you worked on is relevant to the role. Hiring managers just want to know that you have the know-how and passion for learning what it takes to become a successful data engineer for entry-level positions.

Tailor your resume for each job​

We know, it's the news you didn’t want to hear. Unfortunately, customizing your data engineer resume for each job you apply to drastically improves your chances of getting an interview.

Fortunately, only 15 percent of data engineers customize their resumes for each job, so if you go that extra mile, you’re in the top 15 percent automatically (#math)!

How do you tailor your resume for a given job? First, read the job description, responsibilities, and qualifications. Do any projects you’ve worked on come to mind as you read those?

Similarly, does anything come to mind as you read about the company? Even if what you’re thinking about seems like a stretch, it’s worth including on your resume.

Another way to assess is by asking yourself how you can best frame your work experience to be relevant to the role for which you’re applying. For example, if you’re applying for a position seeking someone to build ETLs from scratch and have experience working for startups, you should talk about that as much as possible!

Here are some ideas for tailoring your work experience to a specific role:

AWS data engineer resume tips

  • If you’re looking for an AWS data engineer role, you should be able to show you know the right tool or framework to use at the right time.
  • AWS has so many different services and data offerings that it will make your head spin. Rather than trying to demonstrate a knowledge of all these tools, show the context in which you’ve used the tools with which you’re most comfortable.

Azure data engineer resume tips

  • If you’re comfortable with any other cloud provider, you most likely can adapt to Azure. Having Azure on your resume will allow you to apply to any role looking for a data engineer with Redshift or GCP experience.
  • Azure is the classic example of “if you know one, you know them all."

Big data engineer resume tips

  • We don’t mean to burst your bubble, but “big data” is a nonsense phrase used by business professionals to convince themselves that they know what they’re discussing.
  • Including “big data” on a resume is a bit of a red flag for any discerning hiring manager. It makes the hiring manager think the data engineer is more buzz than substance. Only use "big data" if you can quantifiably back it up with solid metrics.
  • Stick to tangible outcomes and results. Rather than saying “big data” on your resume, include the actual scale of data with which you worked. Again, numbers speak louder than words.

Data Engineer Resume FAQs​

1. What should you include in a data engineer resume?

Only include hard skills (for example MongoDB, Azure, and RDS) in your resume skills section that you’re comfortable discussing in an interview. In your work experience section, use numbers to convey the impact of prior work (like how you used ETL processes to reduce workload by 13%). And finally, tailor your resume to the job by highlighting projects that speak to the challenges and needs of the data engineering position you’re hoping to snag.

2. What skills should you put on a data engineer resume?

Read the job description to see what the company specifically wants in its next data engineer. Consider any programming languages, data processing, SQL, NoSQL, storage, orchestration tools, cloud providers, and AWS tools mentioned in the job ad, and in a brief list, honestly include the skills you have that match.

3. What should a resume look like for a data engineer?

Your one-page resume should look professional—free of grammar and spelling errors and organized in a reverse-chronological format to share your data engineer career history logically and clearly. Using a resume template can help you order your data engineer experience and qualifications.

Resume Examples​

Data Engineer​

Big Data Engineer​

Senior Data Engineer​

Data Analytics Engineer​

Data and Platform Engineer​

Data Engineer Analyst​

Entry-level Data Engineer​

Mid-level Data Engineer​

Lead Data Engineer​

Power and Performance Data Engineer​

Remote Data Engineer​

Computer Vision Data Engineer​

Senior Business Intelligence Data Engineer​

References​

  1. 13 Data Engineer Resume Examples That Work in 2022
  2. 8 Data Engineer Resume Examples - Here's What Works In 2022
  3. Data Engineer Resume Examples | 4 Templates & Advice for 2022
  4. Data Engineer Resume: Sample and Guide (20+ Tips)
  5. Data Engineer Resume Example & Writing Guide
  6. 7 Tips to Build a Job-Winning Data Engineer Resume in 2023
Last updated on by sparsh