Business Intelligence Analyst - Analytics Engineer

🇺🇸Remote - Atlanta$85K–$135K/yri31min ago

Corporate Engineering Data Engineering Business Intelligence Analytics Machine Learning Revenue Operations

Role Snapshot

This hybrid Analytics Engineer role at Turnitin bridges complex data infrastructure and business strategy by supporting RevOps leaders while migrating workflows from Alteryx to dbt. The position also drives AI/LLM and SageMaker-based predictive analytics initiatives such as churn prediction and lead scoring.

Key Responsibilities: Build and document tested dbt data models in Redshift, manage Dagster or Airflow pipelines, and translate technical outputs into business insights for Sales, Marketing, and Customer Experience leaders. Support ABM and Customer Health scoring initiatives with Tableau KPI reporting.

Skills & Tools: Strong SQL and data modeling skills with dbt, Redshift, Dagster/Airflow, and Tableau, plus interest in AI/LLMs and machine learning (SageMaker). Key soft skills include strong stakeholder communication, translating technical concepts for non-technical leaders, and ownership of code quality.

Qualifications: Experience in analytics engineering, business intelligence, or a related data role is expected, with hands-on work building production data pipelines and models. Specific degree requirements were not stated in the posting.

Location: Remote - Atlanta

Compensation: $85K–$135K/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.