When applying for any data analytics or data management role, your resume must present you as a capable authority. Given the rapidly evolving nature of the tech sector and the skills required to work as an industry professional, all sector resumes are naturally held to the same high standards.
What you might not know, however, is that there are particular ways to optimize your CV, depending on your industry role. A data engineer would want to present their unique industry experience to show they’ve tailored their career pathway specifically for data engineer skill sets.
To give your data engineer resume the strongest chance of passing Applicant Tracking Systems (ATS), follow the definitive guide we’ve laid out below. Here are our top formatting and structuring recommendations to help ensure your data engineer resume makes a strong first impression on prospective employers within the analytics industry.
How to Format Your Data Engineer Resume?
Did you know that most ATS scanners are designed to read resumes in .docx format? This can be tricky for data engineers, as the many components of your resume are best formatted with the flexibility of .pdf file types. Sadly, there is a chance that if your resume is submitted as a PDF, it may not be readable to the employer’s ATS.
Suppose you’ve built your data engineer resume using a PDF maker. In that case, we highly recommend converting your CV file from PDF to Word before submitting it to any application portal. That way, you can ensure your PDF formatting stays intact, but your data engineer resume is still readable by the ATS as a .docx file type.
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Key Components of a Data Engineer Resume
The next question you may have when designing a data engineer resume is what components you should include in your CV layout. The structure ensures your data engineer resume is easy to read with a quick skim. Still, it also provides plenty of information for recruiters to inquire about later if your application progresses to the interview stage. Hence, your data engineer resume should ideally include 7-8 key components. These components are as follows:
1. Header
The header of your data engineer resume should include your name, job title, and contact info. Your name should be printed in bold block letters, and your job title should be right below it, much like a subtitle.
For your contact information, ideally include your mobile phone number, best email address, and the URL for your professional website, portfolio, or LinkedIn profile. You may be unable to fit all your experience onto the 1-2 pages of your data engineer resume.
However, a link that allows recruiters and prospective employers to explore more of your work can be valuable. It helps you appear more established in the industry. It also shows your commitment to securing professional opportunities that align with the career path outlined in your CV.
2. Professional Summary
Want to speak more about your experience and ambitions in your own words? That’s what your professional summary is all about. In just 1-2 lines, your professional summary should outline your experience, notable projects, industry accomplishments, and any other skills or accolades you’d like to highlight that set you apart from other applicants.
Keep in mind you’re absolutely allowed to boast in your professional summary. Just make sure to keep it short, because when it comes to resume formatting, less is always more.
3. Work Experience
A common mistake when designing a data engineer resume is failing to provide enough context for your listed professional experience. Prospective employers need to understand your core responsibilities to assess if you’re a good fit for the role you’re applying for.
All the professional experience on your data engineer resume should include the following details:
- Your job role
- The name of the company/organization
- The duration of your time within that role
- The core responsibilities/competencies of that role
Much like any other CV, the best way to arrange all the work experience in your data engineering resume is by starting with the most recent role first and then working backward chronologically. This arrangement is optimal for recording your career progression as a data engineer.
4. Projects
From data analytics to data science and even engineering roles, working within data management typically means working on highly structured ad-hoc projects. So, it stands to reason that you’d want to outline all the projects you’ve contributed to as a data engineer on your industry CV.
Much like speaking on your work experience, your project overviews should include:
- The title of the project
- The scope/details of the project
- Challenges faced during project completion
- Unique skills gained during the project
Providing supporting documentation on projects you’re particularly proud of is also vital, so include any relevant resources in your career portfolio.
Adding plenty of information about the data projects you’ve worked on can be very helpful. It allows recruiters and employers to understand your work style. This highlights your experience with collaboration. It shows your ability to apply industry skills in different contexts. It also reveals what professional success and job satisfaction mean to you.
5. Skills
Your professional experience (including project overviews) is the context in which your industry skills are applied. With this in mind, there are two ideal ways to showcase your skills on your data engineer resume:
- By highlighting them in your work experience (i.e. when speaking on your core responsibilities/competencies)
- In a separate ‘Skills’ section that lists core skills in dot point format
Determining which skills are worth showcasing should be done with consideration to the current role you’re applying for. Generally speaking, there are some universal core skills that recruiters expect data engineers to have.
These include data infrastructure skills, algorithm development, and proficiency with data frameworks. In the next section of this guide, we’ll dive deeper into the key competencies you should include in your data engineering resume.
6. Certifications
For data engineers, certification can help demonstrate your experience using particular frameworks and digital platforms. Most employers would be looking for a data engineer experienced with the platforms or frameworks used within their enterprise, obtaining relevant certification can naturally help your application go that extra mile.
Here are some examples of certifications that could enhance your data engineer resume:
- Google Professional Data Engineer
- AWS Certified Data Engineer
- Microsoft Azure Certified Data Engineer
- Cloudera Certified Professional (CCP) Data Engineer
- IBM Certified Solution Architect
Be sure also to provide all details concerning your certification (i.e. certification name, issuer, year of obtainment, and key skills acquired to qualify for said certification).
7. Academic History
Much like your industry certification, the academic history section of your data engineer resume should include the names of your courses, course providers, and the year you obtained each qualification. Your educational qualifications should also be listed in chronological order, starting with the most recent first.
It’s also imperative that you highlight only relevant academic qualifications in your data engineering CV. While there is some value in sharing your college entrance exam results, these more outdated scores don’t take precedence over the GPA you maintained in your relevant tertiary courses.
8. Industry References
Finally, as data engineering requires extensive collaboration, it’s always beneficial for data engineer resumes to include a diverse range of industry references. These references can be direct supervisors, project managers, company stakeholders, peers, or mentors.
Including your industry references in your CV is optional, however, as some candidates may still refrain from adding these contacts out of respect for their privacy. Suppose you do want to add industry references. In that case, however, we recommend fitting them in at the very bottom of the last page of your CV, as calling your references would likely be the final step of any recruitment process.
With all these key components of a data engineer CV outlined, let’s move on to the essential skills to include in your resume.
Key Competencies to Include in Your Data Engineer CV
As data engineers must develop multidisciplinary skills throughout their academic and professional careers, data engineer CVs must maintain a well-defined scope that effectively highlights a candidate’s wide range of key competencies. The best way to do this is to present key competencies as the takeaways from all the professional and academic experience you’ve outlined in your resume.
Doing this can help demonstrate how you’ve been able to not only apply your skills in hands-on contexts but also how you’ve used your professional experience as opportunities for upskilling. Employers value self-motivated talent, as their investment in you is guaranteed to give rise to your own investment in yourself.
Here are the key competencies you should include in your data engineer resume, and how best to showcase these skills within the professional and academic experience outlined in your CV.
1) Data Infrastructure Skills
Whether you’re working as a pipeline architect or an integration specialist, most professionals with a background in data engineering will naturally want to showcase their data infrastructure skills. These skills include:
- Creating and maintaining data pipelines
- Optimising ETL (Extract, Transform, & Load) data processes
- Designing and developing databases
- Data filtration
Demonstrating your familiarity with structured, semi-structured, and fully unstructured data sets can also help recruiters gauge your range as a data engineer.
2) ML Algorithm Development
As they’re typically tasked with developing data analytics solutions and integrated storage processes, data engineers are naturally expected to be machine learning and AI experts. Data engineers who are proficient in creating ML algorithms that aid in extracting meaningful insights from data sets will be recognized as a vital investment for any data-forward enterprise. Not to mention that ML, AI, and automation are all excellent high-power terms to add to your industry resume.
3) Collaboration (with Data Scientists/Devs Teams, etc.)
In digital-ready organizations, nearly all departments use business data solutions. As a result, data engineers must collaborate closely with various professionals, including data scientists, data analysts, account managers, and other business stakeholders.
Good data engineers should excel in collaboration and communication. They need a deep understanding of each stakeholder’s unique data needs and know how to tailor their data solutions to meet these needs effectively.
4) Capability Using Data Frameworks (i.e. Hadoop, Spark, etc.)
As Big Data becomes a vital investment for larger corporations and small to medium-sized enterprises, companies expect data engineers to be proficient with distributed data processing frameworks like Hadoop, Spark, and Flink, to name a few. Providing information on your professional experiences using these frameworks will likely make you a stronger candidate for recruiters.
5) Facilitating Business Data Flows
Data engineers engage in various tasks, from data model evaluation and natural language processing to collating and presenting performance reports for company stakeholders. Those who can contextualize their work within the goals and expectations of their wider enterprise are undoubtedly valuable assets to any workplace.
This concludes our guide on how you can design an optimal data engineer resume. The next section will cover a few commonly asked questions relating to data engineer CVs. If you have more queries, please drop them in the comments section or contact us directly.
FAQs
Q: How long should a data engineer resume be?
A data engineer resume should ideally only be 1-2 pages long, as overly long CVs risk being disengaged to read or making candidates look disorganized. Keep your data engineer resume concise, ensuring you only highlight skills and experience relevant to the role you’re applying for.
Q: Is data engineering a good role for graduates?
Data engineers are in high demand, with average salaries over $100,ooo USD for experienced candidates. With digital transformation trends, the industry is currently experiencing widespread growth. There are ample professional opportunities available for data engineering graduates.
Q: How do I start a career in data engineering?
To engage with the fundamentals of data engineering, you can either study online, enroll in a formal university course, or self-learn by using the growing number of digital resources available for entry-level data engineers.
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