Analytics Engineer, FinTech

Cloudflare • San Francisco, CA

2d

About The Position

We are looking for an Analytics Engineer to join our FinTech Data Science team who cares deeply about data quality and usability. Sitting at the intersection of data engineering and analysis, you will be the architect of our data layer. While our Data Scientists focus on automating decisions, you will focus on the "truth" of the data — ensuring that the tables and dashboards powering our decisions are accurate, accessible, documented, and reliable. You will transform raw tables into canonical data models and own the presentation layer that leadership uses to monitor the health of our business. If you are excited to build the foundational data infrastructure that powers a multi-billion dollar fintech operation, we would love to hear from you!

Requirements

• 5+ years of experience in Analytics Engineering, Data Engineering, or related roles working with big data at scale.
• Expert-level SQL and proficiency in a high-level scripting language (e.g., Python, R, or Scala) for data automation and manipulation.
• Experience with workflow management tools (e.g., Airflow) to schedule and monitor complex data pipelines.
• Strong experience with dbt or similar frameworks for transforming data in the warehouse.
• Deep experience with BI tools (e.g., Looker, Superset, or Grafana) and a strong understanding of how to structure data for downstream consumption.
• Solid foundation in software best practices, including version control (Git), CI/CD, and data testing/quality frameworks.
• Ability to operate comfortably in a fast-paced environment and take ownership of projects with minimal oversight.
• Excellent communication skills with the ability to bridge the gap between technical engineering terms and business requirements.
• A learning mindset and exceptional curiosity—eagerly diving into new domains and bringing informed ideas to the table.

Nice To Haves

• Experience in FinTech

Responsibilities

• Build out the canonical data schema for FinTech and related organizations by designing and maintaining well-structured, modular, and user-friendly data tables.
• Design, develop, deploy, and operate high-quality production ELT pipelines and data architectures, integrating data from various sources and formats.
• Architect and maintain the presentation layer in BI tools (e.g., Looker/Superset) to ensure dashboards are performant and provide a seamless self-serve experience.
• Act as a strategic partner to stakeholders by translating vague business questions into concrete technical solutions that drive business value.
• Ensure data is accurate, complete, and timely by implementing robust testing, monitoring, and validation protocols for your code and data.
• Establish and share best practices in performance, code quality, data governance, and discoverability while participating in mentoring initiatives.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed