Data Engineer ATS Keywords

Top ATS keywords for Data Engineer resumes — the pipeline tools, cloud platforms, and action verbs applicant tracking systems screen for.

Essential Keywords

Technical Skills

Data Pipeline DevelopmentETL/ELTData ModelingSQL OptimizationData WarehousingStream ProcessingData Lake ArchitectureChange Data Capture (CDC)Data Quality TestingDimensional ModelingPythonScala

Soft Skills

Cross-functional CollaborationStakeholder CommunicationProblem SolvingDocumentationMentoringPrioritization

Tools & Software

Apache SparkApache AirflowdbtSnowflakeDatabricksApache KafkaBigQueryRedshiftFivetranPostgreSQLTerraformDocker

Certifications

AWS Certified Data Analytics — SpecialtyGoogle Professional Data EngineerDatabricks Certified Data Engineer ProfessionalSnowPro Core CertificationAzure Data Engineer Associate (DP-203)

Action Verbs for Data Engineer Resumes

ArchitectedPipelinedMigratedAutomatedOptimizedOrchestratedIngestedTransformedScaledReduced

Industry Terms

LakehouseMedallion ArchitectureData ContractsExactly-Once SemanticsIdempotencyData LineageSchema EvolutionPartitioningData GovernanceSLA/Freshness Monitoring

How to Use These Keywords

1

Mirror the exact platform names in the posting (Snowflake vs. BigQuery vs. Redshift) — data engineering ATS filters are platform-specific.

2

Pair every tool keyword with a scale metric ('Airflow orchestrating 40+ DAGs', 'Spark jobs over 2TB daily') so human reviewers see depth behind the match.

3

Include both 'ETL' and 'ELT' — different companies search different terms for the same work.

4

List orchestration (Airflow) and transformation (dbt) tools separately from compute (Spark) — postings filter on each layer.

5

Add cost optimization language ('reduced warehouse spend') — it's an increasingly common search term as cloud bills grow.

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