Dynamic Data Engineer with 8 years of experience, adept at transforming complex data into actionable insights that drive strategic decision-making. Expertise includes designing real-time data pipelines, developing automated monitoring systems, and implementing data warehousing solutions that enhance data availability. Proficient in technologies such as SQL, Apache Spark, and Hadoop. A collaborative team player with a proven track record of delivering high-quality data solutions within tight deadlines. Passionate about exploring new technologies and methodologies to improve data engineering practices and drive innovation.
12/2019 - present, Data Engineer, IBM, Auckland
- Implemented a real-time streaming pipeline that enabled near-instantaneous event processing
- Developed an automated data monitoring system to detect and alert on data anomalies
- Designed and implemented a business intelligence system that enabled data-driven decision-making
- Developed an automated data warehousing solution that improved data availability by 10%
- Optimised database queries for improved performance, resulting in a 70% reduction in response time
- Supported the development and testing of new software applications, ensuring a smooth transition to production
01/2017 - 07/2019, Data Engineer, Google, Sydney
- Implemented a data pipeline that automated the collection and transformation of large datasets from multiple sources
- Developed an auditing system that accurately tracked data changes and provided detailed insights into data quality
- Designed a search engine that enabled users to easily find and access data
- Developed a data warehouse that enabled users to easily query complex datasets
- Utilised object-oriented programming to create a reusable codebase, resulting in a 65% reduction in development time
01/2015 - 08/2016, Programmer, ATLM Solutions, Auckland
- Developed a web application with a modern user interface that improved user engagement by 15%
- Implemented a data-driven dashboard that provided real-time insights into system performance
- Developed a mobile app that improved customer satisfaction ratings by 20%
- Developed an automated testing framework that improved code coverage to 30%
- Developed a RESTful API that enabled users to access data and services from external sources
- Collaborated with cross-functional teams to identify and resolve software-related issues
02/2012 - 07/2016, Bachelor of Science, University of Auckland, Auckland
- English
- Spanish
- Te Reo Maori
- Communication Skills
- Microsoft Excel
- Project Management
- Scala
- Data Analysis
- SQL
- Apache Spark
- Hadoop
- Machine Learning
- 11/2014, Big Data Engineering with Apache Spark, University of Auckland
- 06/2015, AWS Certified Solutions Architect - Associate, Amazon Web Services
In the competitive field of data engineering, your CV needs to shine. Our guide equips you with the tools and knowledge to build a CV that stands out.
We'll provide expert advice, compelling CV examples, and a user-friendly CV builder that makes crafting a professional data engineer CV effortless.
How to write a data engineer CV:
Your CV is your first opportunity to showcase your data engineering expertise to potential employers.
To make sure your data engineer CV makes a lasting impression, include the following sections:
- The CV header
- The CV personal statement
- The employment history section
- The skills section
- The education section
To craft a data engineer CV that stands out in New Zealand's competitive job market, it’s also a good idea to keep the following strategies in mind:
- Highlight your contributions using metrics and numbers to demonstrate the value you delivered
- Focus on including a range of technical skills and soft skills in your CV
- Opt for a CV format that is clean, well-structured, and easy to read
- Customise your CV for each job application to demonstrate your alignment with the role's requirements
Bypass the ATS
Applicant Tracking Systems (ATS) are a key part of the hiring process. To ensure your CV gets seen, optimise it for the ATS by mirroring the language of the job description.
Identify the core skills and technologies mentioned – for example, "AWS," "Python," and "data pipelines" – and weave them naturally into your skills section and work experience.
Choose the best CV format for data engineers
Your software engineer CV should be a reflection of your unique skills and experience. While a chronological CV format is the most typical format, a combination or functional CV format can highlight your strengths if you have career gaps or limited work experience.
Whether you choose to emphasise specific projects, technical skills, or career progression, select a CV format that effectively captures the attention of potential employers.
Include essential contact information
Your CV header is the first thing recruiters see, so make it count. Present your contact information clearly and professionally, showcasing your meticulous approach to detail.
Be sure to include the following:
- Full Name & Title: Your full name and the specific title you're applying for.
- Email Address: Be sure to use a professional email address that includes your full name.
- Phone Number: Provide a current phone number with a professional voicemail greeting.
- Location: Include your city or town and indicate if you're open to relocating.
- Professional Websites: Include links to any professional websites, such as LinkedIn.
Build a strong professional statement
Your professional statement is your opportunity to make a strong first impression on employers and expand upon your value as a data engineer. In a few sentences, highlight your key skills, career experience, and accomplishments.
Focus on the results you've achieved and how your expertise has benefited previous employers. For example: “Results-driven data engineer with 3+ years of experience designing, building, and maintaining data pipelines for large-scale data processing.”
Need more tips to help craft an engaging professional statement? Check out our related CV examples:
Highly motivated and detail-oriented University of Auckland graduate with a strong foundation in data engineering principles. Eager to begin a career as a data engineer, bringing proficiency in programming languages, data manipulation tools, and cloud technologies. Seeking an entry-level data engineering role where I can apply my skills and contribute to a dynamic team. Passionate about building scalable and efficient data solutions for clients.
Dynamic Data Engineer with 8 years of experience, adept at transforming complex data into actionable insights that drive strategic decision-making. Expertise includes designing real-time data pipelines, developing automated monitoring systems, and implementing data warehousing solutions that enhance data availability. Proficient in technologies such as SQL, Apache Spark, and Hadoop. A collaborative team player with a proven track record of delivering high-quality data solutions within tight deadlines. Passionate about exploring new technologies and methodologies to improve data engineering practices and drive innovation.
Highly accomplished data engineer with extensive experience in architecting and implementing complex data solutions. Proven ability to lead and mentor data engineering teams, drive innovation, and deliver impactful results. Deep understanding of data warehousing and data governance principles.
Highlight your career experience
Don't just tell potential employers what you've done—show them what you've achieved. Instead of simply listing technologies and responsibilities, highlight your accomplishments and the impact you've made as a data engineer.
Each bullet point in your work history section should tell a story of how you used your skills to solve a problem, improve a process, or deliver valuable results.
For example, instead of:
- "Worked with cloud platforms."
- "Developed data pipelines."
- "Built data models."
Try:
- "Migrated on-premises data infrastructure to AWS, resulting in a 20% reduction in infrastructure costs.”
- "Developed and optimised ETL pipelines using Apache Spark, reducing data processing time by 15% and improving data quality."
- "Built robust data models for a new customer analytics platform, leading to a 10% increase in conversion rates."
Highlighting your achievements and quantifiable results effectively demonstrates your value and helps you stand out to potential employers. Ka pai!
Data Engineer at IBM, Auckland
December 2019 - Present
- Implemented a real-time streaming pipeline that enabled near-instantaneous event processing
- Developed an automated data monitoring system to detect and alert on data anomalies
- Designed and implemented a business intelligence system that enabled data-driven decision-making
- Developed an automated data warehousing solution that improved data availability by 10%
- Optimised database queries for improved performance, resulting in a 70% reduction in response time
- Supported the development and testing of new software applications, ensuring a smooth transition to production
Data Engineer at Google, Sydney
January 2017 - July 2019
- Implemented a data pipeline that automated the collection and transformation of large datasets from multiple sources
- Developed an auditing system that accurately tracked data changes and provided detailed insights into data quality
- Designed a search engine that enabled users to easily find and access data
- Developed a data warehouse that enabled users to easily query complex datasets
- Utilised object-oriented programming to create a reusable codebase, resulting in a 65% reduction in development time
Programmer at ATLM Solutions, Auckland
January 2015 - August 2016
- Developed a web application with a modern user interface that improved user engagement by 15%
- Implemented a data-driven dashboard that provided real-time insights into system performance
- Developed a mobile app that improved customer satisfaction ratings by 20%
- Developed an automated testing framework that improved code coverage to 30%
- Developed a RESTful API that enabled users to access data and services from external sources
- Collaborated with cross-functional teams to identify and resolve software-related issues
Discuss relevant data engineer skills
Your skills section is your chance to showcase your diverse technical and analytical abilities as a data engineer.
Don’t forget to include a strong command of technical skills, including computer skills and relevant tools and technologies.
Additionally, don’t forget to include soft skills that enable effective collaboration and communication. Other key data engineer skills include:
- Communication Skills
- Microsoft Excel
- Project Management
- Scala
- Data Analysis
- SQL
- Apache Spark
- Hadoop
- Machine Learning
Detail your education & relevant certifications
The education section of your data engineer CV should highlight your qualifications and commitment to continuous learning in the data engineering field.
List your academic credentials in reverse chronological order, starting with your most recent degree or diploma.
This section is also ideal for showcasing relevant training and certifications:
- Training and Certifications: Include any data engineering-specific courses, workshops, or certifications you've completed. Consider highlighting certifications from major cloud providers, including AWS, Azure, GCP, or in big data technologies, such as Hadoop or Spark.
-
Professional Development: Mention any professional development activities you've undertaken, such as attending data engineering conferences, workshops, or webinars. Membership in professional organisations like IT Professionals New Zealand can also demonstrate your commitment to the field.
Qualifications: If you have any NZQA-approved qualifications or certifications relevant to data engineering or IT, be sure to highlight them.
Bachelor of Science, University of Auckland, Auckland
February 2012 - July 2016
Choose the right CV layout for a data engineer CV
Your data engineer CV should reflect your technical expertise and meticulous approach to data.
Choose a professional or modern CV layout that presents your qualifications in a clear and concise manner, and use a professional font that is easy to read, such as Arial, Calibri, or Helvetica.
Avoid excessive, loud colours or graphics that may distract from the content.
Your CV layout is a reflection of your professionalism and attention to detail–essential qualities for a data engineer.
Data engineer text-only CV example
Profile
Dynamic Data Engineer with 8 years of experience, adept at transforming complex data into actionable insights that drive strategic decision-making. Expertise includes designing real-time data pipelines, developing automated monitoring systems, and implementing data warehousing solutions that enhance data availability. Proficient in technologies such as SQL, Apache Spark, and Hadoop. A collaborative team player with a proven track record of delivering high-quality data solutions within tight deadlines. Passionate about exploring new technologies and methodologies to improve data engineering practices and drive innovation.
Employment history
Data Engineer at IBM, Auckland
December 2019 - Present
- Implemented a real-time streaming pipeline that enabled near-instantaneous event processing
- Developed an automated data monitoring system to detect and alert on data anomalies
- Designed and implemented a business intelligence system that enabled data-driven decision-making
- Developed an automated data warehousing solution that improved data availability by 10%
- Optimised database queries for improved performance, resulting in a 70% reduction in response time
- Supported the development and testing of new software applications, ensuring a smooth transition to production
Data Engineer at Google, Sydney
January 2017 - July 2019
- Implemented a data pipeline that automated the collection and transformation of large datasets from multiple sources
- Developed an auditing system that accurately tracked data changes and provided detailed insights into data quality
- Designed a search engine that enabled users to easily find and access data
- Developed a data warehouse that enabled users to easily query complex datasets
- Utilised object-oriented programming to create a reusable codebase, resulting in a 65% reduction in development time
Programmer at ATLM Solutions, Auckland
January 2015 - August 2016
- Developed a web application with a modern user interface that improved user engagement by 15%
- Implemented a data-driven dashboard that provided real-time insights into system performance
- Developed a mobile app that improved customer satisfaction ratings by 20%
- Developed an automated testing framework that improved code coverage to 30%
- Developed a RESTful API that enabled users to access data and services from external sources
- Collaborated with cross-functional teams to identify and resolve software-related issues
Skills
- Communication Skills
- Microsoft Excel
- Project Management
- Scala
- Data Analysis
- SQL
- Apache Spark
- Hadoop
- Machine Learning
Education
Bachelor of Science, University of Auckland, Auckland
February 2012 - July 2016
Excelling as a data engineer in New Zealand requires a unique blend of technical expertise, analytical thinking, and problem-solving skills.
Streamline your application process and try our online CV builder to start crafting a polished, professional CV. Get started today!