You can build a data pipeline that ingests multiple data sources; you’re great at creating tools that everyone in your company can use. From data analysts to executives, you make the ETLs so they can easily consume data. You’re a master at thinking through the many complicated steps of turning messy data into something usable.
All in all, you’re a great data engineer.
You shouldn’t also have to be great at writing a resume or a data engineer cover letter, but that’s what it takes to get a data engineer job.
These data engineer resume templates are proven to help professionals land jobs at great companies like Stripe and Facebook. We’ll also give you a few expert resume tips to ensure you put your best foot forward to help you land your next data engineer role in 2024.
Why this resume works
- Your data engineer resume works best by illustrating a well-defined career path within a data-driven resume format.
- Start your data engineering career by pursuing a bachelor’s degree in computer science. According to current job-seeking best practices, having a bachelor’s degree is a fundamental starting point guaranteed to land an applicant an internship.
- Once you have at least an internship’s worth of job experience, the sky’s the limit. If you’ve chosen to remain at an internship for several years, moving to a mid-level position at another company becomes attainable.
- Your proven history of dedication and experience alone will pay off excellently when you’re moving from intern/junior to mid-level. From there, experience and skills are the only deciding qualifiers needed to continue climbing the ladder of seniority.
Why this resume works
- Your entry-level data engineer resume can take many shapes and forms; however, a few essentials can make it rise above the rest.
- A bachelor’s degree in computer science is a versatile tool to leverage, while an excellent GPA will catch the reader’s eye, underscoring your work ethic while in school.
- You can also add any awards you won in school, especially if they relate to engineering and computer science.
- And if you have any resume-relevant interests and hobbies, you can add them to highlight skills like curiosity, a passion for learning, and dedication (Plus, this gives you fun things to talk about in the interview!)
- Complementary to your bachelor’s degree, internships exist to provide current students and recent graduates with real job experience. While some internships and apprenticeships exist outside academia, a majority of employers require you to be a current or aspirational degree holder.
- You can also consider using a resume objective as an entry-level candidate to highlight your strengths in a potent, quantified nutshell that introduces your abilities and adds to an otherwise short resume.
Why this resume works
- A mid-level position, regardless of industry, can be an extremely delicate situation to navigate. The fragile nature is due to mid-levels already having a substantial proven history of driving value and being on the cusp of senior-level positions, and needing to finalize their career niche.
- When writing your mid-level data engineer resume, consider two main things:
- The first is asking yourself where you have most enjoyed the time spent in your previous positions.
- The second is where you would like to further hone your career path in aspiring for a specialized senior position.
- By analyzing your answers to those two questions, you will be able to leverage current market data to hone your resume skills and guide future learning toward your desired path of seniority.
Why this resume works
- When it comes to your senior data engineer resume, formatting is your friend.
- Using a resume template will automatically format your resume according to industry standards, but if you choose to build your own resume, learn some resume formatting tips, such as putting your most recent position at the top of the page to ensure the hiring manager reads it.
- Want to show leadership, team management, and other relevant skills? Learn how to complement the job description.
- Start by scanning the job description for the position you want, then move on to other senior data engineer job descriptions. This will help you discover skills that will satisfy most senior data engineers, which you can then include in your skills section and bullet points.
Why this resume works
- In IT recruiting, the average amount of time a reader will spend on any given resume is roughly six seconds.
- This minuscule amount of time spent per resume is what serves as the primary motivation for writing a detailed resume summary for your lead data engineer resume.
- Similar to a resume objective, a career summary exists to inform the reader (recruiter, hiring manager, etc.) of your qualifications, your interest in the position, and your relevant personality traits in an easy-to-understand format. However, a summary is for those who have 10+ years in the industry and want to highlight their specializations.
- When writing a career summary, focus on what makes your experience unique. What certifications do you have? What makes your goals for the position different from other candidates?
- Include quantifiable metrics wherever possible to give further overview and insight into your career without taking up too much space.
Why this resume works
- Engineering the data that drives the world’s cloud computing platform of choice is no small feat. Your AWS data engineer resume needs to prove competency in the service before companies can trust you to support it from the inside.
- Any experience working with AWS should go straight to the top of your resume. It’s the fastest way to establish yourself as an expert in the platform.
Why this resume works
- Constructing cloud-based business solutions is your bread and butter. But to specialize in Azure, you need to build a case for your own qualifications. Highlighting a platform-specific certification on your Azure data engineer resume is a strong place to start.
- Evidence your expertise in Azure to set yourself apart from the field of accomplished data engineers.
Why this resume works
- As a big data engineer (BDE), you collect and analyze information that organizations are generating at unprecedented scales. Because BDEs interact with massive data processing systems and databases in large-scale computing environments, you have a complementary skill set that illustrates a proven history of sweeping data to find relevant groups for analysis.
- Because of this skillset, your big data engineer resume needs to focus on one big (pun intended) thing: data.
- Quantifiable metrics are always a best practice when it comes to your resume, but BDEs take that to the extreme. By highlighting massive amounts of raw data for the resume reader, you instill confidence in your proven history. Adding these details isn’t as hard as it sounds, but our free resume checker can assist if you’re in doubt.
Why this resume works
- When updating your resume skills section on your senior business intelligence data engineer resume, there are two primary sources of data you must collect.
- The first is the job description’s list of required skills. This will give you the exact keywords needed to include in your resume (provided you possess those skills).
- Sometimes, data engineer job descriptions don’t include tidy lists of skills they require, but they do list requirements and expectations. Read between the lines to find skills they would need in their new hire.
- The second data source is senior business intelligence data engineer job descriptions focused on a specific geographic location. After evaluating the market’s desired skill requisites, you can adjust your expertise to the general “heartbeat” of what hiring managers in a given area are seeking.
Why this resume works
- Gather and analyze skill requirement specifics and corresponding KPIs from job descriptions and include them on your power and performance data engineer resume. This will provide you with a roadmap for success!
- Management is a great skill to include, whether it’s self-management, managing a few team members, or supervising an entire department. Talk about a proven leadership experience to set you apart from other candidates.
- Formatting matters when you want to make the experience of the person reviewing your resume as pleasant as possible.
- Pick a Google docs template or a resume template that looks tidy and highlights your strengths in the order best suited to the position.
Why this resume works
- When relevant on-the-job experience is limited, you must rely on degrees, certifications, and skills.
- Additionally, a junior to mid-level role that you’ve held for several years will further prove a historical ability of driving value.
- When developing your career, it’s inevitable (and essential) to build your proficiencies. Yet, including too many, too few, or unrelated skills can easily trip the resume reviewer’s defense system.
- You can design your data engineer analyst resume with a singular target role in mind. For example, if you convince the employer you have all the relevant skills for the job, you can easily land an interview, even if your years of experience are below the “ideal candidate” minimum.
Why this resume works
- Most hiring managers and recruiters won’t spend much time reviewing your computer vision data engineer resume, so the quantifiable data bullet points should demonstrate your outstanding capability.
- Quantify the impact you’ve brought to your previous computer vision data engineering roles within a resume template that promotes your professionalism. For example, did your data acquisition and visualization indicate any major trends? Was the data utilized on a massive scale or from a unique source?
- These can be rough estimates, as the main goal is to showcase your ability to drive high value in your positions. And again, strut your stuff in style with pre-made templates like our free Word resume samples or editable Google docs resumes.
Why this resume works
- Early career data engineers need to take every opportunity to demonstrate the depth and breadth of their industry knowledge.
- The first opportunity you can take is to demonstrate your competency by building well-designed projects that solve real problems through code.
- The key here isn’t reinventing the wheel but creating something dynamic and unique that can’t be easily replicated with a few Google searches and a video tutorial.
- The second option is to invest as much time and effort into your first role as possible.
- When properly navigated, your first role will help define the rest of your career and help you secure any relevant position in the future.
- The key is to properly articulate your hard work, effort, and attention to detail in an organized way.
- We suggest a reverse-chronological resume format to successfully showcase your most current work history first on your remote data engineer resume.
Why this resume works
- While a data engineer’s overall job field description can be quite broad, your data & platform engineer resume must do an excellent job of honing in on a specific career trajectory complemented by quantifiable data.
- Whenever and wherever possible, it’s paramount to include key metrics and quantifiable high-performance indicators. In the broad data field, numbers and data are your “raison d’être” or your “reason for being.”
- Consider including a resume summary if you’re senior enough to have 10+ years in the field.
- Ensure your summary’s top-notch by customizing it to the target business, mentioning the company by name, and including relevant job description keywords.
Why this resume works
- Due to the vast range of skills potentially required in a data analytics engineer role, it’s necessary to “analyze and specialize.”
- Analyze data engineer job descriptions and take note of consistent skill requirements. These can serve as a roadmap of what to include in your data analytics engineer resume.
- You can proactively optimize your resume for the ATS (Application Tracking System) by matching keywords (skills) commonly found in the majority of data engineer job descriptions.
- Specialize by taking the list of consistent skills and narrowing them down into a personalized resume skills section of 10 or fewer skills you possess. Pick the ones you’re most comfortable talking about in an interview to maximize your effectiveness.
Related resume guides
Writing 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:
- 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.
- 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.
- 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.
- 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.
- If you have a particular interest in the role or company to which you’re applying
- You’re undergoing a career change
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
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 using 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.
Running out of room? Save the extra details of how you used ETL processes when using a cover letter maker.
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.
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.
