The Motley Fool
Senior Business Intelligence Engineer
United States - Remote · Senior
Sponsorship not specified$80k-$95kDetected 8 days ago
PythonCode ReviewGitSQLBigQuerySnowflakeRedshiftDatabricksCI/CDMachine LearningAirflowdbtData EngineeringData ScienceData VisualizationLLMsStatisticsA/B TestingProject ManagementJiraCommunicationCollaboration
About the role
- For 30 years, we've been helping people make better investment decisions through transparency, education, and a healthy dose of Foolish fun.
- We're a fast-moving, collaborative team that values high-quality work, curiosity, and initiative.
- We care deeply about what we do, and we're driven by the impact our work has on real people's financial futures.
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.
- Apply ML engineering practices to productionize predictive models, support feature engineering pipelines, and facilitate audience segmentation and targeting workflows.
Requirements
- You enjoy digging into systems to understand how they work and thrive when solving a hard infrastructure or data modeling problem.
- Consider yourself both a builder and a scientist, capable of designing systems that are both technically rigorous and business-oriented, with the ability to tell powerful stories through data.
- 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.
- Strong experience with cloud data warehouses (such as Snowflake, BigQuery, Redshift, or Databricks), including performance tuning and cost optimization.
- Bachelor's degree, preferably in computer science, data science, engineering, statistics, or a related field.
Nice to have
- Experience or familiarity with financial services/investing, digital publishing, direct response marketing, or subscription product environments.
Skills
- Advanced proficiency in SQL for complex querying, data modeling, and robust pipeline development.
- Deep expertise in data transformation frameworks such as dbt (or equivalent).
- 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).
- Education: Bachelor's degree, preferably in computer science, data science, engineering, statistics, or a related field.
- Nice-to-Have/Pluses:
Compensation
- Below is our target compensation range. While we are budget conscious, we're also eager to find the right person for this role, so if your target is outside of this range, please don't hesitate to apply and we'd be happy to have a conversation.
- Hourly Pay Range
Benefits
- Monitor data pipeline health by proactively identifying data quality issues and implementing robust observability and alerting frameworks.
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