Data Engineer Resume Example
A senior data engineer in Seattle with ten years in data, who started as an analyst at a bank and now leads pipeline work for an online grocery delivery company.
A fictional resume written by our team. The person, employers and numbers are invented; the tools, licenses and schools are real.
Why it works
- 1
“Data engineer with 10 years in analytics and data platforms, the last 4 leading pipeline work for an online grocery company. Own a Snowflake and dbt platform of about 1,100 models from 70 sources, used by 400 people.”
Years, stack, scale and who depends on the work. A hiring manager can place the level of this engineer from two sentences.
- 2
“Own a Snowflake platform of about 1,100 dbt models from 70 sources via Fivetran and Kafka, used by 400 people”
Scale and stack in one line: models, sources, how data comes in and who relies on it.
- 3
“Moved 45 nightly batch jobs to incremental dbt models, cutting the daily load from 5 hours to 65 minutes”
A runtime before and after with the number of jobs. Faster loads mean fresher data for everyone downstream.
- 4
“Met a 7am freshness SLA on 99.2% of days in 2025 for the finance and operations dashboards”
A reliability number tied to the people it serves. Data teams are judged on whether the numbers show up on time.
- 5
“Rewrote 20 legacy SQL Server ETL jobs in Python and Airflow on AWS, retiring 3 on-prem servers”
A migration with a count and something switched off at the end, which shows the work actually finished.
How it scored
We ran this example through the same free roast you can use, three times, and kept the middle result. The roast ranks a resume against a typical applicant pile and grades hard: even a resume with a number in nearly every bullet usually lands in the B range.
Copy the text
Use it as a skeleton, then replace every line with your own work. A copied bullet with someone else's numbers is the fastest way to fail an interview question.
Ellery Chaudhry Senior Data Engineer, Analytics Platform Seattle, WA | ellery.chaudhry@example.com SUMMARY Data engineer with 10 years in analytics and data platforms, the last 4 leading pipeline work for an online grocery company. Own a Snowflake and dbt platform of about 1,100 models from 70 sources, used by 400 people. EXPERIENCE Senior Data Engineer, Puget Basket | Jan 2022 - Present - Own a Snowflake platform of about 1,100 dbt models from 70 sources via Fivetran and Kafka, used by 400 people - Moved 45 nightly batch jobs to incremental dbt models, cutting the daily load from 5 hours to 65 minutes - Cut Snowflake spend 29% in 2025 by right-sizing warehouses and clustering the 12 largest tables - Met a 7am freshness SLA on 99.2% of days in 2025 for the finance and operations dashboards - Built a Kafka to Snowflake stream for order events, about 30 million a day at under 5 minutes of lag - Added dbt tests and CI checks to the 80 most-used models, catching 37 breaking changes before deploy in a year - Lead 3 data engineers and run the on-call rotation Data Engineer, Cascade Ledger Bank | Jun 2018 - Dec 2021 - Rewrote 20 legacy SQL Server ETL jobs in Python and Airflow on AWS, retiring 3 on-prem servers - Built the daily loan data feed for the risk team's credit models, with row-count and schema checks on every run Data Analyst, Cascade Ledger Bank | Jul 2016 - May 2018 - Automated 14 weekly Excel reports with SQL and Python, saving the team about 10 hours a week EDUCATION AND CREDENTIALS AWS Certified Data Engineer Associate, 2025, SnowPro Core Certification, 2023 B.S. Statistics, University of Washington, 2016 SKILLS SQL, Python, dbt, Snowflake, Apache Airflow, Kafka, Fivetran, Terraform
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