Compensation

: $100-125k base + bonus based on experience and location What is Reach Financial? Reach Financial is a financial services provider that is helping people outsmart debt for good. We deliver innovative financial products using modern technology and tools to enable our customers to take control of their debt and de-mystify their personal finances.

Our platform empowers our customers to turn their financial goals into a reality. Reach Financial launched in 2015 and has helped our customers pay off over $1 billion in debt. 5T opportunity.

In time, we will expand beyond these products to offer solutions for a variety of our customers’ personal finance challenges.

About The Role

As a Data Engineer II, you will be a key contributor to Reach's data platform modernization efforts. Working closely with Data Engineering, Analytics, Product, and Platform Engineering teams, you will design, build, and maintain reliable data pipelines, transformations, and models that power reporting, analytics, and operational decision-making. This role is ideal for an engineer who can independently deliver solutions to well-defined problems, participate in technical design discussions, and continuously improve the quality and reliability of our data ecosystem.

What You'Ll Do

Design, build, and maintain scalable data pipelines, transformations, and data models using modern ELT practices Participate in incident response and operational support activities, including occasional off-hours coverage for critical production issues, data incidents, and major platform deployments Develop and support data assets that enable reporting, analytics, and operational workflows Participate in technical design discussions and contribute to implementation planning and solution documentation Collaborate with analysts, data scientists, software engineers, and business stakeholders to understand

Requirements

and deliver effective data solutions Troubleshoot data quality, reliability, and performance issues across data pipelines and systems Monitor and improve existing implementations by identifying gaps, inefficiencies, andopportunities for automation Contribute to engineering best practices around testing, version control, documentation, anddata quality Support deployment and maintenance of data pipelines through established CI/CD processes Participate in code reviews and provide constructive feedback to peers Continuously develop technical expertise and apply new tools, techniques, and approaches where appropriate

What We'Re Looking For

Required Qualifications

3–5 years of hands-on experience in Data Engineering, Analytics Engineering, or a relateddata-focused role Experience working in a product-oriented data squad, partnering closely with Product,Analytics, and Engineering to deliver end-to-end data solutions and data products Experience working with modern data platforms and tools such as dbt (Core or Cloud),Amazon RDS, PostgreSQL, or similar technologies; strongly preferred: experience withSnowflake (our primary data warehouse platform) Strong SQL skills with experience developing data transformations and data models Experience building and maintaining ETL/ELT pipelines Experience with Python or a similar programming language Understanding of data modeling, warehousing concepts, and relational databases Experience using Git-based development workflows Ability to independently manage assigned workstreams and deliver high-quality solutions Strong communication, collaboration, and problem-solving skills Demonstrated ability to learn new technologies, tools, and business domains and apply themeffectively

Nice To Have

Experience preparing and modeling data for analysis in Tableau, Sigma, or other BI tools Experience with reverse ETL / data activation tools such as FiveTran activations, Hightouch,etc Familiarity with dbt coding conventions and Medallion data architecture (