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TurnItIn

Business Intelligence Analyst, Revenue Operations

TurnItIn
🇵🇭Remote - Manila, Philippines₱720K–₱1.1M/yri17h ago
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Role Snapshot

Lead the modernization of Turnitin's Revenue Operations analytics foundation by migrating legacy workflows to governed dbt models on Redshift, owning the data pipelines and models that drive insights for Sales, Marketing, Customer Experience, and Finance.

Key Responsibilities: Design and migrate Alteryx workflows into documented dbt models with clear lineage, own orchestration and monitoring in Dagster/Airflow, optimize Redshift performance, and build data foundations for RevOps initiatives like account-based marketing and predictive modeling.
Skills & Tools: Expert proficiency in dbt, Redshift, SQL, and data orchestration tools (Dagster/Airflow); strong analytical mindset with ability to challenge requirements and trace issues to root cause; familiarity with AI/LLM tooling in data engineering workflows.
Qualifications: 5+ years of data engineering or analytics engineering experience with proven expertise in modern data stack tools; demonstrated experience building scalable data models and pipelines in cloud data warehouses.
Location: Remote - Manila, Philippines
Compensation: ₱720K–₱1.1M/yr (estimated)

Job Description

Turnitin's Revenue Operations team is modernizing its analytics foundation — moving to governed dbt models on Redshift and building a trusted, consolidated view of the business for Sales, Marketing, Customer Experience, and Finance.

You own the models, pipelines, and tests that everything downstream depends on. You're not a ticket-taker: we expect you to understand why a metric matters before you model it, and to say so when the requirement as stated will produce a number that's technically correct and practically wrong.

This is an early-stage function, so you'll have unusual influence over how it's built.

What You'll Do:

  • Lead the migration of legacy Alteryx workflows into documented, tested dbt models on Redshift.
  • Design models with deliberate grain and clear lineage, building toward a certified set of marts that reporting reads from.
  • Own orchestration, monitoring, and alerting in Dagster (or Airflow), and the ingestion layer feeding it.
  • Keep Redshift fast and cost-effective.
  • Trace issues to the right root cause — reporting, data model, or upstream business process — and route each to the right fix.
  • Build the data foundations behind RevOps initiatives such as account-based marketing, customer health scoring, and predictive work like churn and lead scoring.
  • Use AI and LLM tooling thoughtfully in the engineering workflow, and help the team form a view on where it belongs.

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