Analytical Data Engineer (Contract)

About The Motley Fool

The Motley Fool is a purpose-driven financial services company on a mission to make the world smarter, happier, and richer. For 30 years we’ve been helping people make better investment decisions through transparency, education, and 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.

About the Data Team

The Data Team at The Motley Fool provides the trusted data foundation for the entire business. Our Analytical Engineering function bridges the gap between data engineering and analytics, ensuring that data is not only collected and processed but also modeled, documented, and made accessible for analysis, experimentation, and decision-making.

Role Overview

This is an independent contract role at 40 hours per week for at least 6 to 12 months, and is best suited for a mid-to-senior level engineer with 4-5+ years of relevant experience. This role focuses on building and optimizing the data layer that powers analysis and decision-making across the Fool. You’ll design and implement scalable data models, ensure quality and governance, and work closely with analysts and stakeholders to deliver business-ready data sets. You’ll take a proactive approach to making data more usable, reliable, and efficient across the company.

Responsibilities

• Design and maintain scalable, business-friendly data models and curated datasets in Snowflake
• Build and optimize data pipelines and transformations using SQL and Python
• Build reusable data assets, including views and table functions for self-service analytics
• Partner with data architects, data scientists, business intelligence analysts, and stakeholders to capture business rules and requirements
• Develop and orchestrate workflows in Airflow (or similar tools) to ensure reliable, automated data delivery
• Diagnose data issues by tracing SQL lineage end-to-end and resolving them at the source, ensuring downstream consistency
• Collaborate with analysts, data scientists, and product teams to translate business requirements into effective data structures
• Implement proactive data validation, quality checks, and monitoring to ensure accuracy and reliability
• Document data models, lineage, and definitions to promote self-service and trust in data
• Automate data enrichment and integration workflows to reduce manual work
• Continuously evaluate and improve data infrastructure, anticipating future business needs
• Stay up-to-date on emerging data tools and analytical engineering practices, and recommend improvements

Required Experience

• 5-7 years of experience with cloud data warehouses, with at least 3 years hands-on experience in Snowflake
• 4+ years of experience in data engineering, analytics engineering, or similar data-focused role
• Knowledge of data warehousing concepts including Star/Snowflake schemas, slowly changing dimensions, and data marts
• Proficiency in SQL, including advanced joins, CTEs, and window functions
• Experience with Python for data manipulation, ingestion, and API integrations
• Familiarity with workflow orchestration tools such as Airflow
• Ability to work independently and communicate effectively with both technical and non-technical stakeholders

Nice to Have

• Experience working with financial, subscription, e-commerce, and/or time-series data
• Experience with business intelligence tools (Tableau, Looker, Thoughtspot, Power BI) and their integration with Snowflake
• Experience integrating customer data platforms like Segment, including configuring event tracking, managing data destinations, and building pipelines to process behavioral and product analytics data
• Familiarity with data quality and observability tools such as Great