Data Engineer resume example. Plus the keywords recruiters search for.
A data engineer resume that shows reliable data pipelines, lower run times and data people trust — with the SQL, Airflow, dbt and cloud keywords data teams filter on.
Reviewed by Nazir Elmurodov · Updated
/ The example
Data Engineer resume example.
Omar Haddad
Data Engineer
Pittsburgh, PA · omar.haddad@email.com · github.com/omarhaddad
Summary
Data engineer with 5 years building data pipelines for retail and logistics. I design batch and streaming ETL in SQL and Python, model data warehousing layers analysts can use without asking me, and treat data quality as part of the pipeline.
Experience
Data Engineer, Three Rivers Grocery Co. · Feb 2023 – Present
- • Build and maintain 60 Airflow DAGs that load sales, inventory and loyalty data into Snowflake every night
- • Rebuilt the nightly batch as incremental dbt models, cutting run time from 6 hours to 90 minutes and Snowflake credit use by 30%
- • Added dbt tests and freshness checks to 200 models; data incidents reported by analysts fell from 12 to 3 a month
- • Stream point-of-sale events from 85 stores through Kafka so inventory dashboards update within 5 minutes
Junior Data Engineer, Ohio Valley Logistics · Jul 2021 – Jan 2023
- • Wrote Python and SQL ETL jobs on AWS — Amazon S3, AWS Glue and Amazon Redshift — for shipment and billing data
- • Migrated 40 cron-scheduled scripts to Airflow with retries, logging and alerting
- • Designed a star schema for billing data modeling that finance analysts now use for monthly revenue reporting
Education & certifications
B.S. Computer Science, University of Pittsburgh, 2021 · AWS Certified Data Engineer - Associate
Skills
SQL · Python · Airflow · dbt · Snowflake · Kafka · Spark · Amazon S3 · AWS Glue · Amazon Redshift · Git
Omar Haddad
Data Engineer
omar.haddad@email.com · Pittsburgh, PA
github.com/omarhaddad
Summary
Data engineer with 5 years building data pipelines for retail and logistics. I design batch and streaming ETL in SQL and Python, model data warehousing layers analysts can use without asking me, and treat data quality as part of the pipeline.
Experience
Data Engineer — Three Rivers Grocery Co.
Feb 2023 – Present
• Build and maintain 60 Airflow DAGs that load sales, inventory and loyalty data into Snowflake every night
• Rebuilt the nightly batch as incremental dbt models, cutting run time from 6 hours to 90 minutes and Snowflake credit use by 30%
• Added dbt tests and freshness checks to 200 models; data incidents reported by analysts fell from 12 to 3 a month
• Stream point-of-sale events from 85 stores through Kafka so inventory dashboards update within 5 minutes
Junior Data Engineer — Ohio Valley Logistics
Jul 2021 – Jan 2023
• Wrote Python and SQL ETL jobs on AWS — Amazon S3, AWS Glue and Amazon Redshift — for shipment and billing data
• Migrated 40 cron-scheduled scripts to Airflow with retries, logging and alerting
• Designed a star schema for billing data modeling that finance analysts now use for monthly revenue reporting
Education
University of Pittsburgh
B.S. Computer Science · 2021
Certifications
AWS Certified Data Engineer - Associate
Skills
SQL, Python, Airflow, dbt, Snowflake, Kafka, Spark, Amazon S3, AWS Glue, Amazon Redshift, Git
Why it works
It sizes the work in pipelines, models and stores, and every bullet ends with something a data team cares about: run time, cost, freshness or fewer incidents. The tools are named precisely, and the AWS certification uses its official name.
Use this as your starting point
Opens in the editor with every section filled in. Swap in your own details and download a PDF or Word file free.
Start from this exampleSample resume. Names, companies and figures are illustrative.
/ Summary examples
Three summary examples. Pick the one closest to you.
Two or three lines: your level, your field and one result.
- Entry level
Computer science graduate with a data engineering internship and a portfolio pipeline that loads public transit data into Postgres with Airflow and dbt. Strong in SQL and Python.
- Mid level
Data engineer with 5 years in retail and logistics. I cut a nightly batch from 6 hours to 90 minutes and dropped analyst-reported data incidents from 12 to 3 a month.
- Senior
Senior data engineer who has led warehouse migrations to Snowflake, set modeling standards for a team of 8 and owns data platform costs and SLAs.
More for other jobs and situations (no experience, career change, senior): resume summary examples.
/ Bullet points
Bullet point examples. From duty to result.
Turn duties into results: what you did, how, and what changed.
Performance
Instead of: Made pipelines faster
Write: Rebuilt a nightly batch as incremental dbt models, cutting run time from 6 hours to 90 minutes
Cost
Instead of: Reduced Snowflake costs
Write: Cut Snowflake credit use by 30% by moving full refreshes to incremental models
Data quality
Instead of: Tested data
Write: Added dbt tests and freshness checks to 200 models; analyst-reported incidents fell from 12 to 3 a month
Streaming
Instead of: Worked with Kafka
Write: Streamed point-of-sale events from 85 stores through Kafka, updating inventory dashboards within 5 minutes
Orchestration
Instead of: Used Airflow
Write: Migrated 40 cron-scheduled scripts to Airflow with retries, logging and alerting
Modeling
Instead of: Designed tables
Write: Designed a star schema for billing that finance analysts use for monthly revenue reporting
/ Keywords
Keywords and skills for data engineers.
These come up often in data engineer job posts. Include only the ones you can back up in an interview, and use the exact wording from the post you're applying to.
- SQL
- Python
- ETL
- Data pipelines
- Airflow
- dbt
- Snowflake
- Kafka
- Spark
- AWS
- Amazon S3
- AWS Glue
- Amazon Redshift
- Data modeling
- Data warehousing
- Data quality
- Git
- AWS Certified Data Engineer
/ ATS tips
ATS tips for data engineers.
Show reliability, not just building
Fewer failed runs, fewer data incidents and on-time freshness matter as much as new pipelines. Put at least one of those in your bullets.
Give run time and cost
Data platform spend is a common concern. A bullet that cut warehouse credits or run time gets attention.
Name the stack exactly
Airflow or Dagster, dbt, Snowflake, BigQuery or Redshift, Spark — recruiters search for each by name. List the ones you've run in production.
Size the data
Number of pipelines, models, sources or stores — or rows and terabytes if you know them — helps a hiring manager judge scale.
Mention who uses your data
Analysts, finance or a product team using your models shows the work mattered beyond the data team.
How does your data engineer resume compare?
Free ATS score, missing keywords and fixes in about 10 seconds.
/ Questions
Data Engineer resume FAQ.
Writing the cover letter too? See Omar's cover letter, annotated
What's the difference between a data engineer and a data analyst resume?
A data engineer resume focuses on pipelines, data models, orchestration and reliability; an analyst resume focuses on the questions answered and decisions made. If you've done both, lead with the side that matches the job.
Are cloud certifications worth listing for data engineers?
They can help, especially when the post names the cloud. AWS offers the AWS Certified Data Engineer - Associate; Google Cloud and Microsoft have their own data engineering certifications. Experience with results still matters most.
Should I include personal data projects?
Yes if you have under about two years of experience. A small end-to-end project — ingestion, transformation, tests and a dashboard — with a GitHub link shows you can build the whole path.
How technical should my bullets be?
Name the tool and the technique — incremental models, CDC, partitioning — and the result. Skip internal table names and detail only your team would understand.
Do I need Spark on my resume?
Only if you've used it. Many data engineering roles now run mostly on SQL in a cloud warehouse with dbt; others rely on Spark. Match the post, and don't list tools you can't discuss.