Business Intelligence Analyst - Analytics Engineer Hybrid (USA Remote)

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.

Essential

• Experience: 5+ years of professional experience in Business Intelligence, Analytics Engineering, or a related data role.
• dbt Expertise: Proven experience building and maintaining production-grade data models using dbt.
• Orchestration Tools: Hands-on experience with Dagster or Airflow.
• SQL & Data Warehousing: Advanced SQL skills and experience with Amazon Redshift (or Snowflake/BigQuery).
• BI Visualization: Experience building stakeholder-facing dashboards in Tableau.
• CRM Knowledge: Familiarity with Salesforce data structures.

Preferred

• Alteryx: Experience with Alteryx (highly beneficial for supporting our migration to dbt).
• AI/ML: Experience with Python and a strong interest (or portfolio) in LLM applications and Machine Learning (Amazon SageMaker).
• Advanced Tableau: Building advanced dashboards and experience with Tableau Online/Server.
• Data Modeling: Salesforce-specific data modeling experience.
• Big Data: Experience dealing with large (+1M rows) customer engagement datasets.