About the job
As a Business Intelligence Analyst at Turnitin, you will play a pivotal role in transforming complex data into actionable business strategies. Your expertise will be utilized in supporting Revenue Operations (RevOps), collaborating closely with leaders in Sales, Marketing, and Customer Experience.
We are in the midst of an exciting transition, migrating our data workflows from Alteryx to dbt. In this role, you will operate at the intersection of data engineering and business analysis. You are not merely a 'dashboard builder'; you are an Analytics Engineer who constructs robust data models in Redshift, manages workflows using Dagster or Airflow, and partners with stakeholders to translate technical outputs into significant business impacts.
Your contributions will extend beyond standard reporting. We seek an individual who is genuinely enthusiastic about the latest advancements in AI and LLM capabilities, aiding us in integrating predictive analytics and machine learning (via Amazon SageMaker) into our RevOps ecosystem.
Key Responsibilities:
- Data Modeling & Migration: Lead the transition of legacy workflows from Alteryx to dbt, ensuring high-quality, well-documented, and thoroughly tested data models that function as a single source of truth.
- Orchestration & Pipelines: Oversee and optimize data pipelines using Dagster or Airflow to ensure reliability and performance within our Redshift warehouse.
- Stakeholder Collaboration: Serve as the primary point of contact between technical data structures and non-technical leaders, translating complex data terminology into clear insights that demonstrate ROI and business impact.
- AI & Advanced Analytics: Research and implement AI/LLM capabilities to enhance data discovery and predictive modeling, collaborating with Product and Engineering to apply Machine Learning (SageMaker) for initiatives such as churn prediction and lead scoring.
- RevOps Strategy: Support high-impact projects such as Account Based Marketing (ABM) and Customer Health scoring by providing visibility into globally recognized KPIs via Tableau.
Key Characteristics for Success:
- The 'Technical Translator': You can articulate complex concepts like joins or latent variables in a manner that resonates with Sales Directors and their objectives.
- Impact-Oriented: Your focus extends beyond delivering data; you convey the 'so what?' behind it.
- AI Advocate: You stay informed about the latest advancements in LLMs and continually consider how to integrate generative AI into analytics workflows.
- Curiosity & Ownership: You lead with inquiries and take pride in the quality and architecture of your code.

