Home Data Engineer Resume template
Data Engineer resume template
A clean starting structure with example content grounded in what data engineers actually do day to day, not generic filler. Download and replace the bracketed placeholders with your own details.
Which resume format should you use?
Reverse chronological
You have a steady work history. This is the format almost every recruiter and ATS expects by default.
Functional
You're changing fields or have gaps in your employment. Leads with skills rather than a job-by-job timeline.
Combination
You're early career or have worked consistently but for only a few employers. Blends a skills summary with a shorter chronological history.
This template uses the reverse chronological format: the one most data engineers should default to, since most Australian recruiters and ATS software expect it.
Professional summary
Data Engineer with a background in building and maintaining ETL pipelines and cloud data infrastructure. Comfortable working across SQL, Python and distributed processing frameworks to deliver data that analysts and machine learning teams can trust. Focused on data quality, pipeline reliability and query performance at scale.
Key skills
- ETL pipeline design and development
- Cloud infrastructure (AWS, Azure, GCP)
- Database schema design and query optimisation
- Apache Spark for distributed data processing
- SQL and Python for data transformation
- Airflow and dbt for orchestration and transformation
- Data quality monitoring and validation
- Networks and systems administration
- Stakeholder collaboration with analysts and data scientists
Experience: example bullet points
- Designed and built ETL pipelines to extract, transform and load data from multiple source systems, reducing manual data handling and improving refresh reliability
- Optimised database schemas and query execution plans for large-scale processing, cutting report generation time and easing load on production systems
- Implemented automated data quality checks and monitoring, catching schema drift and completeness issues before they reached downstream analytics
- Deployed and maintained cloud data warehouse infrastructure on AWS/Azure, supporting consistent uptime for analyst and reporting workloads
- Worked with data analysts and data scientists to translate reporting and modelling requirements into scalable pipeline solutions
- Migrated legacy batch jobs to Airflow-orchestrated workflows, improving pipeline visibility and reducing failed-job troubleshooting time
Education
Typically a bachelor degree in computer science, information technology, data science or a related field; a growing share of the workforce holds postgraduate qualifications, and diploma-level entrants with strong SQL/cloud experience also move into the role.
Keywords an ATS is likely to scan for
Applicant tracking systems match your resume against terms in the job ad before a person ever sees it. Only include the ones that actually apply to your experience, but if a term below matches something you've done, use the same wording the job ad uses.
- ETL
- Apache Spark
- SQL
- Python
- AWS
- Azure
- Google Cloud Platform
- Airflow
- dbt
- data warehouse
- data pipeline
- data quality
- distributed computing
- cloud infrastructure
- database schema optimisation
- data governance
- Australian Privacy Principles
Getting past ATS screening
- Match the specific skills, certifications and terms used in the job ad, not just your own wording for the same thing.
- Keep formatting simple: no tables, text boxes, columns, headers/footers or graphics. Parsers frequently drop content placed in these.
- Submit as .docx or PDF unless the job ad specifies otherwise.
- Use standard section headings (Experience, Education, Skills) rather than creative alternatives.
- List your core skills and technical competencies in their own section so a keyword scan can find them instantly.
This is a starting point, not a guarantee of interviews. Tailor every bullet point to your own real experience and the specific job ad.