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Credit Genie is a mobile-first financial wellness platform founded in 2019 by Ed Harycki (former Swift Capital founder, acquired by PayPal). Backed by Khosla Ventures and led by industry veterans from PayPal, Square, and Cash App, the company provides AI-powered personalized financial insights, instant access to cash, and credit-building tools.
As a Senior Data Engineer, you will independently own the design and operation of scalable data pipelines and platform capabilities across Snowflake and AWS. You will be a core member of the Data Platform & Analytics team, solving complex cross-functional data problems and partnering across the organization to make data reliable, accessible, and ready for growing business and technical use cases.
Key responsibilities include:
- Design, develop, and operate reliable data pipelines for first-party and third-party data across batch, streaming, and CDC patterns
- Lead technical design of ETL/ELT and orchestration workflows, selecting appropriate patterns for performance, scalability, maintainability, and cost
- Develop high-quality SQL and Python solutions for transformation, validation, automation, and complex data processing while setting standards for maintainable engineering
- Design and strengthen data quality, freshness monitoring, alerting, and observability to detect and resolve issues before downstream impact
- Optimize Snowflake workloads, storage, and pipeline architecture for reliability, scalability, performance, and cost efficiency
- Lead investigation of complex production data incidents, identify root causes, and implement durable fixes to improve platform resilience
- Partner with Analytics Engineering, Data Science, Product, and Engineering teams to evaluate source systems, define data contracts, and deliver data products
- Drive and evolve engineering standards and reusable patterns across testing, version control, CI/CD, documentation, schema design, and pipeline development; provide technical guidance and code review
The company expects employees in the office five days per week to foster collaboration and strong culture, though flexibility is available when circumstances require.
Requirements:
- 5+ years of Data Engineering or closely related experience designing, building, and operating production data systems; bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience
- Advanced SQL skills and strong proficiency in Python or similar programming language for data processing, automation, and production engineering
- Strong experience with modern cloud data warehouse (Snowflake) and cloud infrastructure (AWS), including performance, reliability, and cost considerations
- Deep experience with ETL/ELT, orchestration, schema design, and data modeling using tools such as dbt, Airflow, or similar
- Strong understanding of batch and real-time data architectures, including streaming and CDC technologies and their operational tradeoffs
- Demonstrated experience designing data quality controls, testing frameworks, monitoring, observability, and production support practices for critical data pipelines
- Strong working knowledge of Git-based development, CI/CD, automated testing, and modern software engineering practices for data systems
- Demonstrated ability to independently solve complex and ambiguous technical problems, exercise sound judgment, and communicate tradeoffs and recommendations to senior technical and business stakeholders
