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United States
Remote only
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Business Intelligence Analyst – Analytics Engineer Hybrid based in the United States.
In this role, you will bridge the gap between data engineering and business strategy, transforming complex datasets into actionable insights that support revenue growth and operational excellence. You will work closely with Sales, Marketing, and Customer Experience leaders to improve decision-making through reliable data models, analytics, and reporting solutions. A key focus will be migrating legacy workflows to modern data transformation practices while strengthening data quality, documentation, and pipeline performance. You will also explore emerging AI and large language model capabilities to advance predictive analytics and machine learning applications. This opportunity is ideal for a technically skilled, business-minded professional who enjoys solving complex problems, communicating insights clearly, and taking ownership in a collaborative, remote-first environment.
Lead the migration of legacy data workflows from Alteryx to dbt, developing reliable, tested, and well-documented data models that establish a trusted source of truth.
Build, maintain, and optimize data transformation workflows and production-grade models within an Amazon Redshift data warehouse.
Manage and monitor data pipelines using orchestration tools such as Dagster or Airflow, ensuring data reliability, quality, and performance.
Partner with Sales, Marketing, Customer Experience, and other stakeholders to translate technical data concepts into clear business insights and measurable outcomes.
Develop and maintain Tableau dashboards that provide visibility into key performance indicators and support revenue operations strategy.
Support strategic initiatives such as Account-Based Marketing (ABM), customer health scoring, lead scoring, and churn prediction through relevant analytics and reporting.
Explore and implement AI and large language model capabilities to improve data discovery, analytics workflows, and predictive modeling.
Collaborate with Product and Engineering teams to identify opportunities for machine learning applications, including solutions built with Amazon SageMaker.
Maintain high standards for SQL, data modeling, code quality, documentation, and analytical architecture while continuously identifying opportunities for improvement.
At least five years of professional experience in Business Intelligence, Analytics Engineering, or a related data-focused role.
Demonstrated expertise in building and maintaining production-grade data models using dbt.
Hands-on experience with Dagster or Airflow for workflow orchestration and data pipeline management.
Advanced SQL skills and practical experience with Amazon Redshift or comparable cloud data warehouses such as Snowflake or BigQuery.
Experience developing stakeholder-facing dashboards and visualizations using Tableau.
Familiarity with Salesforce data structures and their use in business reporting and revenue operations.
Strong analytical and problem-solving skills, with the ability to turn complex data into practical recommendations and measurable business impact.
Excellent communication and stakeholder management skills, including the ability to explain technical concepts clearly to non-technical audiences.
A proactive, curious, and ownership-driven mindset, with a commitment to data quality, clean code, continuous learning, and collaboration.
Preferred qualifications: Experience with Alteryx migration projects, Python, large customer engagement datasets exceeding one million rows, advanced Tableau dashboards, Tableau Online or Server, and Salesforce-specific data modeling.
AI and machine learning experience: Familiarity with or a strong interest in generative AI, large language models, predictive analytics, and machine learning, particularly applications involving Amazon SageMaker.
Annual base salary: $84,225–$140,375, depending on work location, experience, skills, qualifications, and other relevant factors.
Bonus or commission eligibility, with compensation details confirmed in writing if an offer is extended.
Remote-first working culture that supports flexibility, autonomy, and accountability.
Healthcare coverage and health and wellness programs.
Generous competitive paid time off, national holidays, self-care days, two additional Founder Days, and Juneteenth observance.
Paid parental leave and paid volunteer time off.
Retirement plan with employer match or contributions.
Education reimbursement to support professional development and continued learning.
Monthly wellness or home office reimbursement.
Access to an Employee Assistance Program and mental health support platform.
Charitable contribution matching.
Inclusive, collaborative working environment focused on continuous learning, professional growth, and meaningful impact in global education.