Analytics Engineer

Summary

Join Flex, a rapidly growing finance super app company, as an Analytics Engineer. You will play a key role in building robust data models, ensuring data consistency, and creating documentation for downstream teams. This fully remote position offers the opportunity to work with a talented team and have a significant impact on the company's technical design and engineering culture. You will develop and maintain core data models, collaborate across departments, and drive data quality initiatives. As an early employee, you'll contribute to a vibrant and diverse company culture.

Requirements

• Have 5+ years of working experience working with data, with a focus on data pipeline tools
• Be an expert with SQL and have deep experience working with modern data transformation tools, such as dbt or similar, to create and manage scalable data models
• Have experience building and maintaining data pipelines in cloud-based environments such as Snowflake, Redshift, or BigQuery, ensuring data is easily accessible and reliable
• Enjoy digging into data discrepancies or issues to determine and fix root causes, ensuring high standards of data integrity across the organization
• Have hands-on experience with data visualization tools (e.g., Looker, Tableau, Power BI) to build or support self-serve dashboards that empower non-technical teams
• Have an interest in data quality, including the ability to design systems that ensure accuracy and consistency of key business metrics
• Focus on impact, finding the things you can deliver that deliver the most value for stakeholders
• Have exceptional communication skills, and are comfortable working independently with executive level team members
• Be humble, highly motivated, and thrive in fast-paced environments
• Have a proven ability to proactively manage your own priorities and dependencies in alignment with cross-functional dependencies and product/business impact

Responsibilities

• Develop and maintain core data models in dbt to support key business metrics and ensure data consistency
• Collaborate across departments to define business metrics and ensure proper data infrastructure to serve them
• Ensure downstream teams can access and utilize data effectively by providing comprehensive documentation and support
• Collaborate with other engineers to ensure we’re providing consistent data across the entire organization
• Drive data quality initiatives by building monitoring systems and creating processes that guarantee accurate, auditable data
• Regularly audit and review data models to maintain their relevance and accuracy, ensuring long-term data integrity across the organization