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This post is contributed by Caroline Evans, Burtch Works’ data engineering recruiting specialist.

With data engineers now being a common sight on data teams amongst data scientists and analytics professionals, Burtch Works has been seeing more requests for professionals in this field. We’ve also been getting more requests from the data engineers that we work with, who are looking for information regarding common skills and tools (which I addressed a few months ago) as well as other career tips specifically for data engineers!

One of the most asked-about areas for advice is – you guessed it! – the resume. Since data engineering is such a highly technical field, it can be especially challenging to put together a resume that emphasizes your depth of experience while remaining concise and easy for hiring managers to digest.

As a recruiter that specializes in data engineering roles, I thought I’d share a few tips on how data engineers can create strong resumes.

What Should Be Included on a Data Engineer Resume

1. Include your location and contact information in the header

Make sure to include up-to-date contact information, including your address, the best phone number to reach you, and your email address (preferably a professional-sounding email address, example below).

Example:

John Smith

123 W Division St, Dallas, TX | jsmith123@gmail.com | (999) 123-5555

2. Include your education (degree type and where/when it was earned)

Some employers will want to verify your degree, so make sure to include your degree type as well as where and when you studied (example below).

Example:

EDUCATION

Master of Science, Computer Science, Columbia University, New York, 2008-2010

Bachelor of Science, Electronics and Communications, PSG College of Technology, India, 2000-2004

3. Include a brief summary of your work experience

Summarize your data engineering experience and the value you present as a candidate. This should be no longer than 5 bullet points and not necessarily include every tool and technology you’ve used. Use the summary section to provide a concise picture of your work history and the tools/skills that are the most relevant to the job you’re applying for.

 Example:

SUMMARY

– Over 8 years of professional IT experience, including 5 years of experience in Hadoop ecosystem, with an emphasis on big data solutions.

– Good understanding Talend solution design using of Hive, MapRDB, MapR ES, HBase, TDCH, Teradata, Salesforce, and Mainframe

– etc. etc.

4. Only list tools/technologies that you have experience with

Occasionally I’ve spoken with candidates who’ve listed tools on their resume that they aren’t actually proficient in. This is not only misleading, but won’t actually help you in your job search when you have to explain how you’ve used these tools in your interviews!

Example:

TECHNICAL SKILLS

Platforms: Amazon Web Services (AWS), Microsoft Azure

Databases: MongoDB, RedShift, Oracle, Teradata, Sybase, MySQL

Big Data Tools: Hadoop, Spark, Hive, Pig, Sqoop, Kafka, MapReduce

Languages: Java, Perl, UNIX Shell, JavaScript, Python

Software: Informatica, SSAS, SSIS, MS Project, SPSS

5. Include the company name, location, job title, and dates for your experience

When summarizing your work experience, try to include the tools you’ve used as well as the impact you had, rather than simply listing items as if you’re writing a job description.

Example:

PROFESSIONAL EXPERIENCE

Company Name, Dallas, Texas
Data Engineer

12/2015 – Present

– Data Pipelines: Designed and developed complex data pipelines and maintained the data quality to support a rapidly growing business

– Scripting: Wrote production level code for logging, querying, and media retrieval.

– Product Analysis: Construct ETLs to capture productivity and data quality checks

 

6. If you’re a consultant or contractor, include your company name as well as the client

Make sure you include the company that you are working for as the company name below your job title. Then list the client’s name in the description. As a recruiter or hiring professional, we want to be able to have a clear understanding of where you are working and the nature of your role, as well as the types of clients you’re working for.

Example:

Consulting Firm Name, Dallas, Texas
Data Engineer Consultant

12/2015 – Present

Client: ABC Company
Location: Boston, MA
Duration: 05/2017 – Present

– Data Pipelines: Designed and developed complex data pipelines and maintained the data quality to support a rapidly growing business

– Scripting: Wrote production level code for logging, querying, and media retrieval.

– Product Analysis: Construct ETLs to capture productivity and data quality checks

Client: ABC Company
Location: Chicago, IL
Duration: 12/2015 – 04/2017

– Job description

– etc.

7. Recent grad? Include relevant projects or internship experience

If you’re working on putting together your first or second resume after graduation, it might make sense to include relevant projects and internship experience in the same style as your work experience!

Example – Internships:

PROFESSIONAL EXPERIENCE

ABC Company, Dallas, Texas
Data Engineer Intern

05/2015 – 08/2015

– Data Pipelines: Designed and developed complex data pipelines and maintained the data quality to support a rapidly growing business

– Scripting: Wrote production level code for logging, querying, and media retrieval.

– Product Analysis: Construct ETLs to capture productivity and data quality checks

8. Academic projects listed on your resume should have one or two bullet points describing the project and tools used

Example:

ACADEMIC PROJECTS

Project Title
School/University, Location

1/2014 – 3/2014

– Project description

– Project description

Project Title
School/University, Location

8/2013 – 12/2013

– Project description

– Project description

 

What Should NOT Be Included on a Data Engineer Resume

 

1. Do NOT include photos or your date-of-birth

In my experience, employers that I’ve worked with ask that photos and date-of-birth are not included on a professional’s resume. This is usually due to anti-discrimination laws in the US.

2. Do NOT include every detail of every job and avoid design-heavy formatting

Even if you have a lot of work experience, I still recommend that you keep your resume to 1-2 pages. You should only need 3-4 bullets to summarize each role, and try to focus on experience that is relevant to the role you’re applying for. Since many companies use some sort of computerized applicant tracking system (ATS) which uploads and stores information from resumes, save the design formatting and fancy resume designs for either a job where this is a specific requirement or for your interview presentation, if necessary.

3. Do NOT list your tools at too many times

You do not need to list your tools more than once on your resume. I often see resumes that will list tools on their “summary of skills” sections, in a tools and technologies table (sometimes on the same page!), in their job descriptions, below their job descriptions in a “environment” or “tool” section, etc. As long as you have a tools section, you can include some notes in your work experience, but don’t need to list them so many times.

4. Do NOT omit your education just because it was a long time ago or in another country

Employers will want to see your education and credentials – they matter!

 

It’s always important to remember that your resume is most often your first impression on a potential employer. If you have a clear and concise resume, you’re more likely to get a call back. Overly long and wordy resumes with typos, spacing errors, and weird formatting distract the reader from what is most important…your experience and credentials. Putting the time into creating a well-crafted resume will help you keep the focus on what you bring to the table, and hopefully help you land the interviews and job you want!

Learn more about data engineering job titles and specializations in this post about skills, backgrounds, and job responsibilities.

I hope you found this information helpful, and if you’re looking for opportunities or to hire professionals in data engineering, be sure to connect with me on LinkedIn!

 

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