Lead Analytics Engineer

We are looking for a meticulous and methodical Lead Analytics Engineer to join our Data Science & Analytics team.

Facet is a fully remote FinTech company with a mission to empower people to live more enriched lives by delivering a new standard of financial advice that elevates expectations across consumers and the industry. As a Lead Analytics Engineer, you will enable better insights programs and machine learning features by bridging the gap between our business operations and platform, and our data team. These insights and features will allow us to improve our programs and build a world class member experience.

Core Responsibilities:

• Development and maintenance of core data models, designed for efficient use across Analytics, Data Science, and Machine Learning use cases.
• Efficient orchestration of data models to maximize accuracy and availability, and minimize cost.
• Manage relationships with core technology partners across Data Science & Analytics, Software Engineering, Business Operations, Cybersecurity, and Platform Engineering to ensure our data warehouse is providing the most accurate reflection of our business sources of truth.
• Employ business acumen and analytical skills to identify suspicious system behaviors and results, and track down issues before they impact downstream reporting and model outputs. It’s critical that you learn and understand our business operations and systems to excel in this role.

Requirements

Traits

• Exemplary communication skills, especially when communicating with non-data stakeholders. Your ability to effectively communicate the needs of data functions with other technical leaders will be key to performing this role.
• Very strong troubleshooting and analytical skills.
• Strong customer data privacy knowledge and sensibility.
• Strong aptitude for technology and automation, driven to learn constantly and share knowledge with others.
• Resourceful, creative, and comfortable working in small teams with minimal supervision to solve complex business problems.

Tool Knowledge

• Extensive experience leveraging Python and SQL to solve data problems.
• Familiarity with building and maintaining data models in cloud environments like BigQuery or Snowflake, and leveraging supporting cloud compute technology on GCP or AWS.
• Experience monitoring and managing large projects and budgets on GCP or AWS.
• Advanced knowledge using SQL template engines like dbt and Airflow for constructing end-to-end data transformation pipelines.
• Experience with distributed data systems, such as Apache Spark for handling large datasets.
• Familiarity with machine learning frameworks such as scikit-learn, xgboost, and similar.
• Experience collaborating with other Analysts, …