Click here to directly go to the complete big data resume sample

A professional in big data field should be able to conduct as well as code quantitative and statistical analysis

However, to get a job as a big data professional, you need to optimize your big data analyst resume for the specific jobs. Doing this will help you show that your expertise matches the demands of the job.

The 10 basic resume tips that we have outlined below can help:

If you want someone to lend a hand in your resume writing process, use Hiration’s Online Resume Builder and create stellar Big Data Resumes for yourself.

Also here check out some related profiles which you may be interested in:

Big Data Developer Job Description

Here are common roles and responsibilities of a Big Data Developer:

  • Design data pipelines for extracting and transforming data into products for helping organizations to reach their goals.
  • Develop in Hadoop and create high performance web services for tracking data
  • Research and analyze alternative data processing and storing solutions
  • Train juniors on Big Data and data management by conducting workshops
  • Collaborate with data science team to implement data analysis pipeline
  • Oversee the security and privacy of data

Big Data Developer Salary

Here is a Big Data Salary trend projected by Edureka and Statista:

Big Data Developer Salary Trend

  • According to, the average salary of a big data developer in the USA is $120,000
  • According to the big data developer makes around $108,989 per year in the USA

Big Data Developer Resume Bullet-Points

Candidates mostly struggle to create perfect bullet points for their resumes.

We have created an extensive resource to help you write a Big Data Developer resume. You can simply copy paste the bullet points from these resources and create your resume.

  1. Developed and implemented a database for the purpose of analyzing and reporting on the status of a project
  2. Developed a new database to manage the inventory of over 1,000 products
  3. Developed, implemented and maintained a new stored procedures for the data warehouse and database
  4. Developed new features and enhancements to the ETLS system, including data loading and validation
  5. Developed, maintained and updated the data model for a large-scale, multiyear project
  6. Developed various reports and dashboard to monitor the status of all projects and to track progress
  7. Developed and implemented a custom script to generate reports for the company's website
  8. Developed a database to store and track the number of employees in a company

Click on the links below to use the ready made power bullets for any profile:

Big Data Developer Interview Questions

1. What are the four V's of Big Data?

Here are the four V's of Big Data development:

  • Volume – Related to management of data
  • Variety – Related to various formats of data
  • Velocity – Related to the data growth
  • Veracity – Related to accuracy of data

2. What are the commands for starting and ending Hadoop systems?

Starting Code:

Shutting Down Code:

3. What are the port number of NameNode, Task Tracker and Job Tracker?

  • NameNode – Port 50070
  • Task Tracker – Port 50060
  • Job Tracker – Port 50030

What Is a Big Data Resume?

If you're reading this blog, you're probably aware that the big data industry is crippled with competition.

Almost everyone wants to get their hands on sophisticated big data jobs. After all, that's where the future lies.

So to beat the competition and get shortlisted for a coveted big data job, you will need to stand out. You will need to do more than just make a targeted big data resume.

To enable you to implement them, we have provided section-wise explanations and big data analytics resume samples at the end of each section.

This is done to help you understand not just what to do, but what the end product of your actions will look like in your big data analyst resume.

We can guarantee that by the end of this blog, you will be able to write a stellar big data resume (given you follow each tip).

Opt for One-Page Resume Unless You Have 10+ Years of Work Experience

If you have been wondering what the right resume length for your big data resume should be, we have the perfect answer for you.

Here are some resume length tips for professionals in the USA:

  • Write a one-page resume if your total number of work experience in big data is less than 10 years.
  • Write a two-page resume if you have over 10 years of big data work experience.

This rule applies to professionals in the USA.

However, in European, Asian, African, and most countries of the world; the US resume length standards do not apply.

Here are some resume length tips for professionals in non-US countries:

  • If you have more achievements or points that do not cover the scope of a one-page resume, don't worry. You don't need to cut back on important information just because it does not fit into a single page.
  • Writing a one-page resume is not a strict rule. As long as the extra information adds value to your resume, write it down.
  • If you have mention-worthy big data accomplishments, don't redact it from your resume just because your big data resume is spreading over two pages.

Also Read: Why one page resume is the most preferred length

Use Sections to Articulate Information in your Big Data Resume

Nobody likes to read a big data developer resume that is poorly presented.

If you want a recruiter to take interest in your big data developer resume, the information in your resume should be professionally articulated. Moreover, it should be reader-friendly too.

Using resume sections can help.

You should always use these 7 must-have resume sections to organize your information:

  • Header
  • Personal Information
  • Profile Title
  • Summary/Objective
  • Key Skills
  • Professional Experience
  • Education


If you have more information that does not cover the scope of these sections, you can also use the following add-on sections:

  • Internships
  • Certifications
  • Projects
  • Volunteering Experience
  • Additional Information

Before we proceed, ask yourself these questions:

Have you been using relevant sections in your big data developer resume?
Have you been using sections that you do not need?
Do you need to cut down or do away with irrelevant sections?

Also Read: What are the best must have resume sections?

If you can't answer these questions, you need resume help. Turn to our resume strategists for valuable one-on-one resume advice with our Resume Review Service!

Big Data Resume: Header

The resume header of your big data resume for experienced professionals needs to be correct and on-point.

Hiration pro tip:
Don't make the common mistake of writing 'CV' or 'Resume' right on top. Instead, write your real full name at the top part of your big data resume. Example: 'Dean M. Winchester'

Also Read: What to list in your resume header?

Here's a big data resume sample presenting the ideal resume header for your big data resume for experienced professionals:


This is a snapshot of a big data resume template that is available on our Online Resume Builder.

Big Data Resume: Personal Information

If your big data architect resume gets shortlisted, how will a recruiter reach you?

Through the information, you provide in the personal information section.

This gives you your biggest clue. It shows that you should incorporate your contact information in this section such as:

  • One active contact number to facilitate a telephonic interview.
  • A professional email address to facilitate official communication.
  • Your current location in city/state code format. Example: 'New York, NY'


In addition to this, you can also include the following information:

  • LinkedIn profile URL to facilitate profile vetting.
  • Online portfolio or personal website to showcase your work samples.

Big Data Developer Resume Sample for Personal Information

Personal Information
Contact Number: +1 222 235 3531
Email Address:
Current Location: Los Angeles, CA

Also Read: What to provide in your resume contact information section?


This is a snapshot of a big data resume template that we have made using our Online Resume Builder.

Big Data Resume: Profile Title

Your profile title is necessary because it communicates the following details about you to a recruiter:

  • Your latest or recent job title.
  • The level of your seniority.
  • Your functional industry.
  • Your potential of earning and expected salary.

This means:

  • If you're writing a big data developer resume, you should write your profile title as 'Big Data Developer.
  • If you're writing a big data architect resume, you should write your profile title as 'Big Data Architect'.

A Big Data Architect is a more senior role than a Big Data Developer. This means that a Big Data Architect is entitled to more pay because of the sophistication of the work that comes with the job title.

Given its importance, here's what we want you to do:

  • Write your profile title correctly.
  • Write it in the second-largest font size of 14-16 points to ensure that this a recruiter can spot it immediately.

Here's a big data resume sample showcasing a correctly written profile title for a Big Data Developer Resume:


Big Data Resume: Professional Experience Section

If you are writing a big data resume for 3 year experience jobs, you need an impeccable professional experience section.

When done to perfection, this section alone holds the power to convince a recruiter of the merit of hiring you. Thus, this section needs to be perfect at all costs.

To perfect this section, you'll need to do more than just illustrate your achievements & prove them.

Following these resume tips can help:

  • Write one-liner points to present your big data work experience.
  • include achievement figures, relevant keywords, and suitable power verbs.
  • Use Grouping & Highlighting to enhance the overall impact of this section.
  • Only include relevant achievements in the professional experience section

Here is an example of professional experience section of Big Data Resume:


Use One-liner Points

We advocate the use of one-liner points to communicate the details of your work experience in big data.

Here's why:

They make your resume easy to read.

This is a major plus because:

  • Reader-friendly resumes are more likely to get parsed by an Applicant Tracking System.
  • An Applicant Tracking System is a recruitment software that companies have started using to filter out the least desirable candidates.
  • Your resume will not reach a human recruiter if the ATS does not parse it.
  • To get your resume parsed by an ATS, you need to make use of one-liner points
  • This enhances the readability of your resume, thus enhancing your shortlist chances.

Use Achievement Figures, Power Verbs, and Keywords

Enhancing the readability of your big data architect resume is a must. You now know how to achieve it. But your work does not end here, it simply begins.

Writing reader-friendly resumes won't guarantee shortlist. It will only make your resume more palatable to a recruiter.

Thus, in addition to using one-liner points, you need to do what it takes to make your resume worth reading. Here's what you can do:

  • Use achievement figures
  • Begin each point with a power verb
  • Incorporate keywords wherever possible

Also Read: What are the best resume action words and power verbs?

Achievement figures

Using achievement figures is all about quantifying your achievements. It helps you show that you can add value to an organization.

Be it department growth, or sales, or in this case; creating data models to study the market or attain another goal; achievement figures help you prove the value of your professional contributions.

So instead of saying something as vague as this:

  • Built data models

Describe it by adding relevant figures as shown in the following lines:

  • Built a 100% accurate data model & algorithm to study customer behavior & understand the buyer's persona

Explaining the nature of your work using achievement figures in the second point helps you showcase your efficiency.

In the first point, the user is simply stating that he/she built data models.

In the second point, the user show why he built, and how accurate the model was. Thus, it helps a recruiter understand the expertise & sophistication of the professional. In this case, a Big Data Engineer.

Power Verbs

Power verbs are nothing but professional terms for regular words that fail to make an impact.

Hiration pro tip:
Use power verbs to begin each one-liner word. They help you give a professional tone to your professional contributions.

For example, instead of using a bland word like "Managed", you can use the following power verbs:

  • Oversaw
  • Supervised
  • Administered
  • Directed
  • Governed

Using words like "Directed" or "Governed" instead of a word like "Managed" helps you present the same information more meaningfully & professionally.

Use keywords

Using relevant keywords in this section can help you in the following ways:

  • Using keywords can make your resume ATS-compatible.
  • Most ATS software is designed to look for keywords in your resume.
  • If your resume uses keywords in strategic places, it is more likely to get parsed by an ATS software. This means that your resume is more likely to reach a human recruiter when you use keywords in your big data engineer resume.
  • Human recruiters tend to look for keywords too. Here's why:
  • Most recruiters are not industry specialists. While they are responsible for the recruitment life-cycle, they are not specialists in every field.
  • This means that they too are conditioned to look for keywords in your resume. The more your resume matches a job description, the probability of shortlisting your resume increases too.
  • Thus, you should use keywords in your big data resume.

All you have to do is:

  • Scan through the JD of your target big data jobs.
  • Look for resume keywords: they can be skill-based, education-based, and work-experience-based; or a combination of all three.
  • Of interest to us is a skill-based criterion or keyword.
  • Once you locate them, match them with your skills. If you are skilled in them, place them organically into this section & justify it.

Also Read: How to highlight the right resume keywords?

Grouping & Highlighting

So far you know how to:

  • Make your resume more reader-friendly
  • Make your resume worth reading

Now the third and most important element is to ensure that your resume gets read using resume tips & tricks. grouping & highlighting can help you achieve this.

Here's how:

  • Grouping is the practice of listing similar points under relevant headings.
  • The headings help you communicate the key expertise area of the professional.
  • All a recruiter has to do is read the bucket header to know what the Big Data Engineer specializes in & what his/her key responsibility is.
  • Highlighting is the practice of marking selected words/phrases in bold.
  • All you have to do is here is highlight relevant words, phrases, or numbers/achievement figures by marking them in bold.
  • Doing this makes them stand out.
  • When a recruiter looks through your resume, the words or phrases you have highlighted attracts their attention instantly.
  • This thus helps you divert the recruiter's attention to strategic achievements & career highlights in each point.
  • As such, grouping & highlighting is an effective tool when used alongside one-liner points. We advise you to use them to perfect the professional experience section.

Big Data Resume Sample for Professional Experience

Here's a big data resume example showcasing the professional experience section of a Big Data Developer Resume:


When you follow all the rules of resume writing for this section, your professional experience section would look like this.

This big data sample resume has been created with the help of our Hiration's Online Resume Builder.

Given below is a snapshot of this work experience section from the resume template that is available on our tool.

Big Data Resume: Academic Details

The resume education section is a must-have section of your resume.

This means that whether you are writing a big data resume for 3 year experience or a big data resume for 2 year experience; you have to include this section at all costs.

Despite the number of work experience you may have, your academic background will always be a point of interest to the recruiters. Why? Because they want to know the university you went to and the year you graduated in.

Being from a reputed college also helps advance your job application; so make sure you include these details while drafting this section:

  • Name of the university you have attended.
  • Name of the courses you have pursued.
  • Location of your school/university.
  • Enrolment & graduation dates.

If you are wondering what the education section of your big data experience resume should look like, don't worry. We have got you covered.

Here's a big data resume example showcasing a perfectly composed education section:


This is a snapshot of the education section from the big data resume template that we have made on our Online Resume Builder.

You can easily edit & modify the template by signing up for our Resume Builder!

Separate Your Technical Skills from Your Key Big Data Skills

Do you know how to highlight a big data resume and make it stand out in your resume?

Through the key skills section!

This section helps you endorse both your core big data skills & technical skills in your resume.

Your core big data skills are those skills that you are expected to have by default simply because you are a Big Data Professional. Recruiters will explicitly look for these core big data skills in your resume.

Here is a list of the most sought-after core big data skills:

Big Data Developer Resume Key Skills
Data Analytics Data Visualization
Programming Machine Learning
Data Mining Mathematics
Statistics Algorithm Design
Data Modeling Hadoop System
Big Data Developer Resume Technical Skills
Hadoop Framework: YARN, MapReduce, Apache Pig, Hive, Flume
SQL Framework: MySQL, Oracle DB
NoSQL: Cassandra, MongoDB
Programming Language: Python/R/Java
Big Data Tools: Scala, Hadoop, Linux, MatLab, R, SAS, SQL, Excel, SPSS
Cloud Technologies: Amazon Web Services (AWS), Microsoft Azure, Alibaba Cloud

The above-listed tools are your technical skills. You need to deploy these tools/technologies to execute your Big Data responsibilities.

We suggest that you to create a "Technical skills" subsection under the 'Key Skills' section to differentiate the two.

Also Read: What skills to put on a resume?

Here's a big data resume example showcasing the skills section of your resume:


This big data sample resume shows you how to show big data skills on resume.

Meanwhile, we encourage you to get your big data experience resume reviewed by our Resume Experts at Hiration!

We have helped professionals from around the world get shortlist from coveted organizations. We can help you too!

Big Data Resume Summary

To stand a chance at getting shortlisted, your big data resume summary needs to be bang on!

Concluding your big data resume for experienced professionals with an impeccable Big Data Resume Summary will help you retain the interest of the recruiter.

You can think of your resume summary as a hybrid between great storytelling and a fantastic sales pitch. You need to strike a perfect balance between the two to ensure that:

  • You captivate the recruiter's interest
  • You get your resume shortlisted

Here are some ways you can achieve this:

  • Keep your resume summary short and crisp. A summary that is well articulated has the scope of capturing the recruiter's interest.
  • Expert Advice: Keep your resume 3-5 lines long.
  • Filter out the most relevant career highlights and endorse them in your professional summary statement. Doing this helps you show the value you have brought to your organization. It also helps you communicate that you have what it takes to replicate the same success for the hiring organization too!
  • Start your big data resume summary with your total number of work experience. Example: '5+ years experienced...'.
  • If you have less than 3 years of work experience, write a big data resume objective (not a summary statement).

Also Read: How to compose the perfect resume summary?

Here's a big data resume example showcasing a well-designed big data resume summary.


While you're picking up the skills to resume writing, many professionals are already winning the shortlist game!

Beat the competition with our AI-powered Online Resume Builder.

It is designed to give you the resume help you need!

Know What to Include in a Big Data Resume for Freshers

Now that you know how to write a big data resume for experienced professionals, get started on curating your resume already!

But if you are a fresher aiming to land an entry level job in big data, you should know how to write a big data resume for freshers and what to include in it.

It is important to know the specifics because it is fundamentally different from a generic big data resume for experienced professionals. However, they're also similar in the following ways:

A big data resume for freshers and experienced professionals have the following sections in common:

  • Header
  • Personal Information
  • Profile Title
  • Key Skills
  • Education

For those of you who are writing a big data resume for freshers, here's what you can do:

  • Replace the professional experience section with the internships section
  • Replace the professional summary with an objective statement.
  • Include extra sections such as projects, certifications, and volunteering sections to add weight to your big data resume for freshers.

We have compiled a list of the top 3 add-on sections to include in your big data resume for freshers:

Big Data Resume: Objective

You should write an objective statement if you are writing a:

In other words, if you are a fresher with no work experience, or have less than 3 years of relevant work experience in big data, you should write an objective statement.

Just like the summary section, compose this section at the end.

Try to focus on your big data skills & highlight the achievements of past projects or internships in big data. Doing this will help you show that despite the absence of relevant work experience, you have what it takes to thrive in a full-time job.

Big Data Developer: Internships

A big data resume for freshers is written by IT, computer science, or engineering graduates who don't have any work experience yet. In this scenario, the professional experience section gets replaced by the internships section.

Going with the assumption that you have done relevant internships in your undergraduate days, all you have to do is compile a list of the internships you have done and list them down in this section.

If you don't have any internships, do an internship in data-based roles & mention them in this section post-completion.

Internships matter because they show that despite the absence of relevant work ex, you have some degree of industry exposure. It also shows that you know how to operate in office set-up, thus minimizing the work of the hiring organization.

Here's a big data resume sample showcasing the internship section:


Big Data Developer: Projects

Every tech graduate or undergraduate is expected to do projects as part of their coursework. This makes a perfect add-on to put in your big data resume for freshers.


Because doing projects symbolizes that you are not just equipped with theoretical knowledge. It shows that you armed with relevant practical knowledge too.

All you have to do is compile a list of the projects you have done as part of your coursework.

If you have done additional projects outside of your college or taken part in hackathons or Kaggle projects; feel free to give an account of these projects in your big data resume for freshers.

Knowing how to write big data project in resume is important. Here's how you can do it:

  • Mention project name
  • Mention project duration
  • Mention the goal of the project
  • Mention your project achievements

Big Data Developer :Certifications

Do you know how to show big data interest in resume?

Through the certifications section of course!

Certifications are a great way to demonstrate both your interest in big data and your proficiency in it. More importantly, it shows that you are abreast of the latest trends in your functional niche/industry. In this case, big data.

So if you have relevant certifications to put in your resume, make a list of the following details and arrange them horizontally:

  • Certification course name.
  • Name of the certifying institute.
  • Location of the certifying institute.
  • Certification enrollment & completion dates.

{Name of Certification} | {Affiliating Institution} | {Location} | {Date} (month & year format)

Common certification for Big Data Developer:

Also Read: What all certifications on resume works?

Big Data Developer: Volunteering Experience

If you think that the importance of a volunteering experience begins and ends with getting you into universities, you are wrong.

There is more to a volunteering experience than meets the eye.

For those professionals who are hoping to start their career and settle into a new job, showcasing volunteering experience in your resume can help.

It is a great addition to your big data resume for freshers and we highly recommend it. Here's why:

Volunteering experience helps you highlight your soft skills. It helps you draw attention to your leadership, team working, and initiative-taking skills - all of which fall under the umbrella of 'soft skills'.

Many organizations are starting to see the merit in them. As such, we advise you to put a volunteering experience section in your big data resume for freshers.

Here's a big data resume example showcasing the volunteering experience section:


Save Your Resume Using a Big Data Resume PDF Format

A pdf format is a better choice than a word format. You should save your resume in a PDF format before sending it to recruiters. Here's why:

  • PDF files support images, graphics, and charts.
  • They retain the structural integrity of your resume.
  • As such, an ATS bot can easily read & parse them.


Taking into account all these factors, we recommend you to use a big data resume pdf format to save your resume.

Unless a hiring organization explicitly asks for a DOC file format, save your resume in a PDF format.

Use Hiration's Resume Services

We take great pride in our Resume Services. We have outlined them below:

  • Resume Review Service
  • Online Resume Builder

Resume Review Service

Your big data developer resume will be reviewed professionally while keeping it in compliance with the given parameters:

  • Compliance with industry norms
  • Content Relevance
  • Recruiter Friendliness
  • Design Compatibility
  • Conversion Scope
  • ATS Compliance
  • Global Compatibility
  • Performance Assessment
  • Resume Formatting (font, margins, the order of sections, etc.)

To get the right resume help, get your hands on our Resume Review Service now!

Online Resume Builder for Big Data Resume Resume PDF Download

Our AI-powered Online Resume Builder is the best that there is. Built with the best of modern technology, it provides intuitive features to help you make a resume that stands out:

  • Auto bold
  • A sharable link
  • 25+ resume designs
  • 100+ pre-filled resume templates
  • LIVE resume score
  • JD-resume matcher
  • Full rich-text editor
  • Unlimited PDF downloads
  • 1-click design change
  • Option to save unlimited resumes
  • Intuitive predictive text suggestion

Moreover, our resume building tool supports big data resume PDf download.

PDF formats are the preferred formats and are ATS-compatible too!

Make a resume that is designed for ATS parsing with our Online Resume Builder now!

Complete Big Data Sample Resume

In case you're wondering what a perfect big data resume looks like, here's a big data sample that is perfectly optimized for resume shortlists:

3+ years experienced Big Data Developer possessing a proven track record of managing Big Data operations. Proficient in liaising with the cross-functional teams to design, build, install, and configure Hadoop. Highly skilled in working on disparate data sets, transforming & loading data between data sources, and analyzing vast data stores to uncover key insights.
• Big Data Analytics • Data Architecture & Processing • Hadoop Designing • Project Management
• Systems Architecture Support • Data Loading • Data Security • Application Designing • Code Review
• Software Development & Management
Big Data & Hadoop: Hive, Flume, MapReduce, Spark, Pig, HBase, Sqoop, HDFS
Languages: Python, Scala, Java, Nodejs, HTML, CSS, JavaScript, C++
Unix Shell Scripts: KornShell, Bash
Database: MySQL, MongoDB

    Data Loading & Hadoop Designing
    • Designed, planned, & developed programs to perform automated extract, transform and load data between data sources
    • Devised, built, installed, configured & supported Hadoop and maintained security and data privacy
    Data Analysis & Application Designing
    • Managed & deployed HBase and performed the analysis of vast data stores and uncovered insights
    • Helped the Application Development team of 25 to design 10+ applications & develop data projects within time
    • Developed & executed implementation according to the project plans and priorities provided by senior staff members
    Data Tracking & Code Reviewing
    • Assisted in working on disparate data sets and created scalable & high‐performance web services for data tracking
    • Reviewed code and provided feedback to the seniors relative to best practices & performance/process improvements etc.
    • Ensured compliance with coding standards & techniques and assisted with establishing standards
      Software Designing & Coding
      • Played a key role in researching, designing, implementing and managing 3+ software programs
      • Tested and evaluated new programs and identified areas for modification in existing programs and developed them
      • Wrote and implemented efficient code and maintained & upgraded the existing systems
        • Cumulative GPA: 4.5/5.0
        • Member of the ICare NGO | Jun '17 - Jun'18
        • Taught Mathematics and Computer Science to 50+ students every weekend
        • Captain of the AIS Football Team | Jun '18 - Jan '20
        • Secured 1st position twice in Dec '18 and Dec '19

        Key Takeaways

        This blog has conclusively answered the following questions:

        • How to highlight a big data resume
        • How to show big data skills on resume
        • How to write big data project in resume
        • How to show big data interest in resume

        Here's a quick overview of the key takeaways of this blog.

        • Your big data experience resume should have 7 must-have sections: Header, personal information, profile title, summary, key skills, professional experience, and education sections.
        • In addition to these sections, you can also add the certifications, internships, projects, and volunteering experience sections. These add-on sections are highly recommended for Big Data professionals who don't have much work experience to showcase in their resume.
        • As a rule of thumb, you need to accurately present your profile title. The failure to this will lead to loss of credibility and potential blacklist from the companies you have tricked.
        • Keep your big data resume summary short & crisp. A 3-5 lines paragraph is more than enough. Make sure that you don't exceed this limit.
        • Write a big data resume objective if you are a fresher or have less than 3 years of relevant work experience in big data.
        • You need to perfect the professional experience section at all costs. To achieve this:
        • Use one-liner points for work experience communication. This enhances the readability of your resume, thus making it both ATS and recruiter-friendly.
        • Add achievement figures to prove your accomplishments. This helps you show the value you have brought to the organization.
        • Incorporate resume keywords wherever possible. ATS bots look for keywords or job criteria in your resume. Incorporating relevant keywords helps you ace the ATS test and enhances your shortlist chances.
        • Use grouping & highlighting to divert attention to strategic words/phrases (mainly achievements in each one-liner point).
        • Volunteering experience, certifications, and internships are extremely helpful for fresh graduates who are looking for entry level big data jobs. Make sure you mention them if you are looking for your first big data job.

        With this, you have reached the end of this blog.

        Go to Hiration resume builder that has 24x7 chat support to assist you in creating a professional resume for yourself. Additionally, reach out to us at

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