Senior Business Intelligence Engineer

The Motley Fool

15h • $80 - $95

About The Position

The Business Intelligence (BI) team at The Motley Fool plays a critical role in designing, building, and maintaining the data infrastructure that powers strategic decision-making across the entire organization. They architect scalable data pipelines, optimize analytical workflows, and deliver reliable, high-performance data products. The team acts as a bridge between technical backend infrastructure and business needs, ensuring the data platform is robust, maintainable, and built so the business can move faster with total confidence.

The Business Intelligence Engineer plays a vital role in driving our data and analytics infrastructure forward. This role will partner closely with data engineers, analysts, product managers, and business stakeholders to architect robust data models, streamline transformation layers, and deliver high-impact insights. This role is ideal for a builder who is fluent in both data architecture and analytics, and who thrives in a fast-paced environment where they can guide data strategy.

Requirements

• 7+ years of experience in data science, analytics engineering, or business intelligence engineering, with a proven track record of building scalable data infrastructure that drives business impact.
• Advanced proficiency in SQL for complex querying, data modeling, and robust pipeline development.
• Deep expertise in data transformation frameworks such as dbt (or equivalent).
• Strong experience with cloud data warehouses (such as Snowflake, BigQuery, Redshift, or Databricks), including performance tuning and cost optimization.
• Experience building and maintaining ELT/ETL pipelines using tools like Airflow, Prefect, dbt, or similar orchestration frameworks.
• Proficiency in Python for data pipeline development, automation, and ML feature engineering.
• Experience with BI and visualization tooling such as ThoughtSpot, Tableau, Looker, or Power BI.
• Experience with Git-based workflows, CI/CD for data pipelines, and Jira (or equivalent project management tools).
• Excellent communication and translation skills—the ability to articulate technical design decisions, trade-offs, and data quality issues clearly to both technical and non-technical audiences.
• Bachelor's degree, preferably in computer science, data science, engineering, statistics, or a related field.

Nice To Haves

• Experience or familiarity with financial services/investing, digital publishing, direct response marketing, or subscription product environments.
• Familiarity with statistical testing, experiment design, A/B testing infrastructure, or ML/AI engineering practices (including model productionization, feature stores, and LLM-based tooling).

Responsibilities

• Serve as a senior BI partner for the Product team, owning data architecture, guiding data strategy, pipeline reliability, and the analytics engineering roadmap in support of business unit goals.
• Collaborate and consult directly with business teams to understand their strategy, economics, and goals, translating business questions into analytical frameworks.
• Design, build, and maintain scalable data pipelines and transformation layers (such as dbt models and ELT workflows) that power dashboards, reports, and ML features.
• Develop and maintain data marts, semantic layers, and self-serve tooling that empowers internal stakeholders to make smarter, faster decisions.
• Partner with analysts and product managers to instrument, design, and support A/B testing frameworks and experimentation infrastructure.
• Monitor data pipeline health by proactively identifying data quality issues and implementing robust observability and alerting frameworks.
• Work closely with data governance and data engineering to ensure data quality, lineage, and strict compliance with organizational standards.
• Apply ML engineering practices to productionize predictive models, support feature engineering pipelines, and facilitate audience segmentation and targeting workflows.
• Champion engineering best practices including peer code reviews, CI/CD for data pipelines, version control, and documentation standards.
• Stay informed about emerging trends in data science, analytics engineering, and the modern data stack.

Benefits

• The Motley Fool will be collecting the personal data you provide for our recruiting purposes. Please see our Applicant Privacy Notice for additional information about how we process, transfer, and store your data, including where that data is stored, and about any additional privacy rights you may have based on your jurisdiction.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior