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Remote role plus recognizable brand and metro candidate pool, but specialized dbt/Redshift/Dagster skills moderate competition.
Core data engineering skills transfer, but RevOps and Salesforce-specific modeling increase domain sensitivity.
Explicit 8+ years plus mandatory dbt, Redshift, Dagster, Python, and Salesforce experience enforces strict filters.
Lead migration of legacy Alteryx workflows into documented, tested dbt models on Redshift, ensuring deliberate grain and clear lineage for reporting.
Own data orchestration, monitoring, and alerting in Dagster (or Airflow), maintaining ingestion layers and optimizing Redshift performance and cost.
Build and maintain data foundations enabling Revenue Operations initiatives like account-based marketing, customer health scoring, churn and lead predictive models.
6-8+ years in Analytics Engineering, Data Engineering, or Business Intelligence with substantial hands-on data modeling responsibility.
Proven hands-on experience with production-grade dbt projects including testing and documentation.
Hands-on experience with Dagster or Airflow orchestration tools and advanced SQL with Amazon Redshift (or Snowflake/BigQuery) including performance tuning.
Strong knowledge of Salesforce data model, proficiency in Python for data workflow automation, and Git-based workflow with code review and CI.
Experienced in building scalable, maintainable data pipelines with emphasis on data quality, including root cause analysis across reporting, modeling, and upstream process issues.
Strategic thinker comfortable translating between business (Sales Director) and technical (engineer) perspectives to deliver impactful, actionable insights beyond just data delivery.
Proactive owner who prioritizes code quality, documentation, and cost-effective data infrastructure supporting early-stage function development in Revenue Operations analytics.