Senior Data Engineer

Reach Financial is a Fin Tech platform helping people outsmart debt for good.

We are building innovative products and best-in-class support that enable our customers to take control of their debt and de-mystify their personal finances. Our products and tools empower 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. We offer debt consolidation loans and personal loans; together, these markets represent a $1.5T opportunity. In time, we will expand beyond these products to offer solutions for a variety of our customers' personal finance challenges.

We are a fast-growing and fast-paced Fin Tech startup with the stability of an established firm. You will have a front-row seat at a rapidly growing company innovating the Fin Tech industry.

As a Senior Data Engineer at Reach, you’ll work alongside our existing Data Engineering team on our data platform modernization effort. You’ll be a key contributor to our broader data practice, building and maintaining pipelines, data models, and transformations as we modernize Reach’s data stack. You’ll help establish scalable, reliable, and consistent data engineering practices across the organization, ushering in a new era of cohesive data design and management within the broader Engineering organization.

• Develop and manage data pipelines, data models, schemas, and data artifacts as a core contributor to our data squad.
• Champion data engineering best practices, including data quality, version control, testing, and documentation.
• Collaborate with Data, Software, and Platform Engineers to evolve and improve existing engineering practices, tools, and infrastructure.
• Partner with data scientists, analysts, stakeholders, and cross-functional data teams across the organization to understand data requirements and translate them into technical solutions.
• Stay up to date on emerging data engineering tools and technologies, and help evaluate new solutions to optimize our data ecosystem.
• Collaborate with Platform Engineers to ensure seamless integration and deployment of data pipelines using shared CI/CD tools and Infrastructure as Code solutions, such as Git Hub Actions and Terraform.
• Monitor and troubleshoot data pipelines, proactively identifying and resolving issues to ensure data quality, reliability, and availability.
• Develop and maintain documentation for data pipelines, data models, and engineering processes.

• 6+ years of hands-on experience in data engineering, working with dbt (Core or Cloud), Snowflake, Fivetran, Amazon RDS, PostgreSQL, etc
• Strong proficiency in dbt development best practices and coding conventions, with hands-on experience designing and implementing Medallion data architecture (Bronze, Silver, and Gold layers) in a production environment.
• Extensive knowledge of SQL and No
  
  SQL data stores
• Experience with data pipeline orchestration tools such as Airflow, Dagster, or similar platforms
• Experience implementing automated data quality checks, dbt testing, and data validation frameworks
• Experience with CI/CD pipelines, Git-based version control, and automated deployment processes for data engineering workflows
• Demonstrated experience optimizing Snowflake performance, dbt models, SQL queries, and data warehouse costs
• Production experience working with and managing a Snowflake deployment
• Experience extracting information from SaaS systems like Salesforce using ETL tools like Five Tran
• Production experience using dbt Cloud or other source-driven transformation management tools
• Experience with Infrastructure as Code and Database Change Management tooling
• Experience with operational database management, including…