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Professional Summary
“Analytics engineer with 4 years bridging the gap between data engineering and analytics. Expert in dbt, SQL, and modern data stack tools with a focus on building reliable, well-tested data models that serve as the single source of truth for business reporting.”
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Key Skills
dbtSQLSnowflake/BigQueryPythonGitData Modeling (Kimball/OBT)Looker/TableauAirflowData Quality TestingSemantic LayerFivetran
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Sample Experience Bullets
- Built and maintained 200+ dbt models with 95% test coverage. These are the single source of truth for all company reporting
- Designed a star schema data model for e-commerce analytics. Queries got simpler and dashboard load times improved 70%
- Set up the dbt CI/CD pipeline with automated tests, doc generation, and freshness monitoring on every PR
- Built a self-service metrics layer with MetricFlow so non-technical users can get their own reports without writing SQL
- Cut data team support tickets by 60% by writing clear documentation, tagging everything in the data catalog, and running training sessions
- Responsible for the weekly data model review where engineers and analysts discuss schema changes and new table designs
- Worked with the finance team to build revenue recognition models in dbt that matched their accounting definitions exactly
- Wrote custom dbt macros for common transformation patterns like SCD Type 2 tracking and incremental model refreshes
- Managed the Fivetran connectors for 15+ data sources. Handled schema drift issues and connector upgrades as they came up
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ATS Keywords
Include these keywords in your resume to pass Applicant Tracking Systems.
analytics engineerdbtdata modelingmodern data stackdata transformationsemantic layerdata qualityELTdimensional modelingdata governance
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Recommended Certifications
- dbt Analytics Engineering Certification
- Google Professional Data Engineer
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