Data Engineer resume example
Data engineering resumes should show that data arrives on time, correct and at a sensible cost. This example covers pipelines, warehouses, data quality and the teams that rely on them, with numbers for volume, speed and reliability.
Called a CV in the UK, Ireland, India, Africa, Australia and many other places, and a resume in North America. The layout below works for both.
Lukas Weber
Data Engineer | Python, SQL, dbt, Airflow | Cloud Data Warehouses
Munich, Germany lukas.weber@example.com
Summary
Data engineer with five years building batch and streaming pipelines for retail and mobility companies. Designs clean data models, automates testing and monitoring, and works closely with analysts and data scientists so they can trust the numbers.
Skills
- Python
- SQL
- dbt
- Apache Airflow
- Apache Spark
- Kafka
- Snowflake
- BigQuery
- Data modelling (star schema)
- Data quality testing
- Terraform basics
- Git and CI/CD
Experience
Data Engineer
Mar 2022 to Present
Velocity Mobility, Munich, Germany
- Built streaming pipelines with Kafka and Spark processing around 50 million vehicle events a day for pricing and operations teams.
- Moved 120 legacy SQL scripts into tested dbt models, reducing broken dashboard incidents by more than half.
- Introduced data quality checks and alerting that catch late or missing data before business users notice.
- Cut warehouse costs by 30% by redesigning large tables and scheduling heavy jobs off-peak.
Junior Data Engineer
Sep 2020 to Feb 2022
Alpenmarkt Retail, Augsburg, Germany
- Maintained 35 Airflow pipelines loading sales and stock data from 200 stores.
- Built a customer data model in BigQuery used by the marketing analytics team.
- Documented every pipeline and owner, which shortened onboarding for new analysts.
Education
MSc Data ScienceIsar University of Applied Sciences, Munich, Germany
2020
Certifications
- Google Cloud Professional Data Engineer
- dbt Fundamentals
Languages
German (native) · English (fluent)
This example is fictional: the person, employers and figures are invented to show good structure. Use it as a guide and write your own, true details.
What makes this resume work
- 1Data volumes and number of pipelines quickly show the scale of the work.
- 2Reliability is measured by fewer broken dashboards, which is what data users notice.
- 3Cost savings in the warehouse are increasingly valued as cloud bills grow.
- 4The stack is listed in the headline, matching how data engineering jobs are searched.
- 5Collaboration with analysts and data scientists is mentioned, because data engineers serve internal customers.
Common mistakes to avoid
- Listing tools without data volumes, frequency or who used the data.
- Ignoring data quality and documentation, which hiring managers often ask about.
- Using the same resume for data analyst and data engineer roles. The emphasis is very different.
Applying for a data engineer job?
Pair your resume with a short, specific cover letter. See the data engineer cover letter example, or draft your own with the cover letter generator.
Questions people ask
What should a data engineer resume focus on?
Pipelines you built, the volume and frequency of data, tools used, data quality and reliability, and who depended on the data.
Is SQL enough for data engineering?
SQL is essential, but most roles also need Python, an orchestration tool such as Airflow, and experience with a cloud data warehouse.
Can a data analyst move into data engineering?
Yes. Start by automating your own data preparation, learning dbt and an orchestration tool, and taking ownership of pipelines your team relies on.