Business Intelligence Analyst - Analytics Engineer

🇺🇸Remote - Dallas, TX$85K–$130K/yriJust now

Corporate Data & Analytics Business Intelligence Data Engineering Analytics Machine Learning Revenue Operations

Role Snapshot

This hybrid Analytics Engineer role at Turnitin bridges data infrastructure and business strategy by supporting Revenue Operations, leading the migration from Alteryx to dbt, and integrating AI/LLM and predictive analytics into RevOps workflows.

Key Responsibilities: Build and document tested dbt data models in Redshift, orchestrate pipelines with Dagster or Airflow, translate technical outputs into business insights for Sales, Marketing, and Customer Experience leaders, and support ABM and customer health initiatives through Tableau dashboards and SageMaker-based ML such as churn prediction and lead scoring.

Skills & Tools: Strong SQL and dbt modeling, Redshift, workflow orchestration (Dagster/Airflow), Tableau, and interest in AI/LLMs and machine learning, combined with the ability to explain complex data concepts clearly to non-technical leaders and focus on business impact.

Qualifications: Experience in analytics engineering, business intelligence, or data modeling, with hands-on work in data warehousing and pipeline tooling; specific degree and years of experience requirements were not stated in the posting.

Location: Remote - Dallas, TX

Compensation: $85K–$130K/yr (estimated)

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Job Description

The purpose of this role is to bridge the gap between complex data infrastructure and actionable business strategy. You will provide day-to-day support to Revenue Operations (RevOps), including Sales, Marketing, and Customer Experience leaders.

We are currently in an exciting transition, migrating our data workflows from Alteryx to dbt. As a BI Analyst, you will sit at the intersection of data engineering and business analysis. You aren't just a "dashboard builder"; you are an Analytics Engineer who builds robust data models in Redshift, orchestrates workflows via Dagster/Airflow, and works directly with stakeholders to translate technical outputs into business impact.

Crucially, you will help us move beyond standard reporting. We are looking for someone genuinely excited about the frontier of AI and LLM capabilities, helping us integrate predictive analytics and machine learning (via Amazon SageMaker) into the RevOps ecosystem.

Key Responsibilities and Outputs

Data Modeling & Migration: Lead the migration of legacy workflows from Alteryx to dbt, ensuring high-quality, documented, and tested data models that serve as a single source of truth.
Orchestration & Pipelines: Manage and monitor data pipelines using Dagster or Airflow to ensure reliability and performance within our Redshift warehouse.
Stakeholder Collaboration & Translation: Act as the primary liaison between technical data structures and non-technical leaders. You will translate complex "data speak" into clear insights that highlight ROI and business impact.
AI & Advanced Analytics: Actively explore and implement AI/LLM capabilities to enhance data discovery and predictive modeling. Collaborate with Product/Engineering to apply Machine Learning (SageMaker) to areas like churn prediction and lead scoring.
RevOps Strategy: Support high-impact initiatives such as Account Based Marketing (ABM) and Customer Health scoring by providing visibility into globally symbols KPIs via Tableau.

Proven Characteristics for Success

The "Technical Translator": You can explain a join or a latent variable to a Sales Director in a way that makes sense for their quota.
Impact-Focused: You don't just deliver data; you deliver the "so what?"
AI Enthusiast: You stay up to date with the latest in LLMs and are constantly thinking about how to apply generative AI to analytics workflows.
Curiosity & Ownership: You lead with questions and take pride in the "cleanliness" and architecture of your code.