Data Engineer

About Us

A fast-growing, data-driven fintech company is building a modern platform focused on improving outcomes in consumer finance. Their technology helps rebuild trust, deliver better results, and support millions of people in achieving greater financial stability. By leveraging data intelligence, they enable more transparent, effective interactions between consumers and financial institutions.

Their mission is to expand access to credit while empowering individuals with greater control over their financial lives. They've built a strong foundation supporting the full lifecycle of consumer debt, combining performance, compliance, and customer experience—and they're continuing to scale.

The Role

As the Founding Senior Data Engineer, this individual will play a critical role in shaping how data is leveraged across the business. They will take ownership of a modern data stack and evolve it into a scalable, best-in-class platform that powers analytics, reporting, and machine learning.

This is a high-impact, 0→1 opportunity where they will define data engineering as a core function, enabling the broader team to move faster and make better decisions.

Responsibilities

• Own and optimize the entire data platform, including a modern cloud data warehouse (e.g., Snowflake)
• Design and build scalable, reliable ETL/ELT pipelines with strong monitoring and observability
• Develop clean, intuitive data models for reporting, dashboards, and ML use cases
• Enable self-service analytics while maintaining security and compliance standards
• Partner with engineering, product, and analytics to ensure high-quality, usable data
• Implement best practices including testing, CI/CD, and documentation
• Help drive strategic decisions on tooling, architecture, and long-term data infrastructure

Key Initiatives

• Redesigning core data models to significantly reduce query redundancy
• Improving pipeline reliability and proactive monitoring
• Optimizing warehouse performance and cost efficiency
• Building semantic layers to unlock data for both technical and non-technical users

Requirements

• 5+ years in data engineering or analytics engineering
• Strong experience with modern data warehouses (Snowflake, BigQuery, Redshift)
• Advanced SQL skills and a deep understanding of query performance
• Hands-on experience with dbt or similar tools
• Proven ability to build and scale ETL/ELT pipelines
• Experience designing scalable, flexible data models
• Experience operating as a sole or lead data engineer
• Strong collaboration with engineering teams on data quality and systems design
• Track record of improving performance while reducing infrastructure costs
• Experience implementing data quality and monitoring frameworks

Skills & Mindset

• Systems thinker with a strong sense of ownership
• Comfortable operating in ambiguity and building from scratch
• Able to connect technical work to business impact
• Clear communicator who values documentation and collaboration
• Bias toward iteration and shipping

Nice to Have

• Experience with real-time/streaming data systems
• Exposure to ML infrastructure or feature stores
• Familiarity with financial data or regulated environments
• Background in startups or high-growth companies