# Senior Data Engineer at Credit Genie

Credit Genie is hiring a Senior Data Engineer. It pays $180k-$210k a year and Level rates it Little AI ●○○○; you can [apply on Credit Genie](https://jobsbylevel.com/go/72835de0-d916-43d2-af1d-4be36d7a34b6?utm_medium=ai-agent).

AI Level 1, AI centrality 27 out of 100. Plymouth Meeting, PA.

## Details

- Company: [Credit Genie](https://jobsbylevel.com/companies/credit-genie)
- AI level: AI Level 1 (score 27 out of 100)
- Location: Plymouth Meeting, PA
- Salary: $180k-$210k
- Posted: September 4, 2026
- Apply: https://jobsbylevel.com/go/72835de0-d916-43d2-af1d-4be36d7a34b6?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=senior-data-engineer-at-credit-genie-78f1d6

## Description

Company Credit Genie is a mobile-first financial wellness platform designed to help individuals take control of their financial future. We leverage artificial intelligence to provide personalized insights and are building a financial ecosystem by offering tools and services that provide instant access to cash, and building credit. Our goal is to empower every customer to achieve long-term financial stability. Founded in 2019 by Ed Harycki , former Swift Capital Founder ( acquired by PayPal in 2017 ). Backed by Khosla Ventures and led by industry pioneers from companies such as; PayPal, Square, and Cash App, we are well positioned to build the future of inclusive finance through cutting-edge technology and customer-centric solutions. Overview Join our Data Engineering team and help shape the trusted data foundation that powers analytics, strategy, and downstream applications. As a Senior Data Engineer, you will independently own the design and operation of scalable data pipelines and platform capabilities across our Snowflake and AWS environment. You will solve complex, cross-functional data problems, exercise strong technical judgment, and partner across the organization to make data reliable, accessible, and ready for a growing set of business and technical use cases. What You'll Do Design, development, and operate reliable data pipelines for first-party and third-party data across batch, streaming, and change data capture (CDC) patterns. Lead the technical design of ETL/ELT and orchestration workflows, selecting appropriate patterns and tradeoffs for performance, scalability, maintainability, and cost. Develop high-quality SQL and Python solutions for transformation, validation, automation, and complex data processing, while setting a strong standard for maintainable engineering practices. Design and strengthen data quality, freshness monitoring, alerting, and observability so issues are detected and resolved before they materially impact downstream users. Optimize Snowflake workloads, storage, and pipeline architecture with attention to reliability, scalability, platform performance, and cost efficiency. Lead investigation of complex production data incidents, identify root causes across systems, and implement durable fixes that improve platform resilience and reduce recurrence. Partner with Analytics Engineering, Data Science, Product, Engineering, and other technical stakeholders to evaluate source systems, define dependable data contracts, and deliver data products that support analytics and downstream applications. Drive and evolve engineering standards and reusable patterns across automated testing, version control, CI/CD, documentation, schema design, and pipeline development; provide technical guidance and code review to other engineers when appropriate. 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 a related field, or equivalent practical experience. Advanced SQL skills and strong proficiency in Python or a similar programming language for data processing, automation, and production engineering. Strong experience with a modern cloud data warehouse such as Snowflake and cloud infrastructure such as 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 technologies. Strong understanding of batch and real-time data architectures, including streaming and change data capture (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

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Source: https://jobsbylevel.com/jobs/senior-data-engineer-at-credit-genie-78f1d6

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