United States onlyThe Motley Fool is looking for a highly skilled Freelance Data Architect specializing in Snowflake to join our team on an independent contract basis, 40 hours per week for at least 6 months. This is a mid to senior level position and requires 4-5+ years of relevant experience.
While this role is flexible and 100% remote, candidates must be located in the United States for consideration.
Who are we?
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.
What does this team do?
The Data Democratization, Governance Strategy team at The Motley Fool is dedicated to making data accessible and actionable for all business end-users. We specialize in the final stretch of data delivery, transforming warehouse data into easily consumable formats. By working collaboratively with third-party vendors and stakeholders, we build data structures that support seamless reporting and valuable business insights. Our close partnerships with business analysts and data engineering ensures that every team at The Motley Fool can leverage data to drive informed decisions and strategic growth.
What would you do in this role?
We are seeking a skilled contractor with expertise in Snowflake's data warehouse platform to re-architect and optimize our reporting layer. The primary focus of this role will be on improving cost efficiency and compute optimization within Snowflake. The ideal candidate will have strong analytic engineering skills and a deep understanding of Snowflake's architecture to streamline data processing, enhance performance, and reduce costs associated with our data reporting.
But what would you actually do in this role?
Snowflake Optimization:
- Evaluate and optimize the reporting layer of our Snowflake data warehouse to enhance cost efficiency and compute utilization.
- Develop and implement strategies to improve query performance, reduce data processing time, and enhance overall efficiency.
- Collaborate closely with the data engineering team to implement optimizations without compromising data integrity or security.
Analytic Engineering:
- Utilize advanced analytic engineering techniques within Snowflake to optimize data transformations and computations.
- Design efficient data models and schemas to support optimized reporting and analytics.
- Implement best practices for data loading, storage, and retrieval to minimize costs and maximize performance.
Compute Efficiency:
- Optimize query performance by tuning Snowflake configurations and query execution plans.
- Implement caching strategies and materialized views to improve response times for commonly used reports.
- Collaborate with data engineers to ensure efficient ETL processes and data transformations.
Required Skills and Experience:
- Proven experience working with Snowflake data warehouse, including optimization projects.
- Strong expertise in analytic engineering techniques within Snowflake, such as query optimization, indexing, and partitioning.
- Deep understanding of Snowflake's architecture, including virtual warehouses, storage optimization, and clustering keys.
- Proficiency in SQL and data modeling for Snowflake.
- Familiarity with ETL processes and data pipeline optimization.
- Excellent problem-solving skills and the ability to troubleshoot complex performance issues.
- Strong communication skills to collaborate with cross-functional teams and stakeholders.
- Self-motivated with a proactive approach to identifying and implementing optimizations.
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.
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