Data engineering resumes live or die on pipeline reliability and scale — the volume of data moved, the latency of the pipeline, and how it survived schema changes and upstream failures.
Purpose-built indigo two-column layout for pipeline engineers and ETL specialists — the closest literal template match available.
A slate layout designed around data integration work, ideal if your experience leans heavily ETL/ELT.
Worth considering if your pipelines feed ML systems directly — this template bridges data infrastructure and ML deployment framing.
The hard skills, tools, and certifications ATS software scans for on data engineer resumes.
If you build and maintain the pipelines others query, you're a data engineer — lead with infrastructure and scale, not analysis or dashboards.
Yes, but be specific ("Spark via Databricks") — it's accurate and still matches ATS searches for "Spark."