Sr. Data Engineer

Address: 322 Rhett Street, Greenville, South Carolina, United States - 29601   

 

Purpose Financial, Inc. is an innovative consumer financial services company that offers a diverse suite of credit products, promoting financial inclusion and meeting consumers wherever they are. Through its brands, the company is committed to helping customers achieve their version of financial stability in the moment and in the future.  Since 1997, Purpose Financial has been a pioneer in the consumer credit and financial services market offering money solutions in over 1,000 storefronts locations and online lending.  Providing services in over 20 states, Purpose Financial employs over 2,700 team members.

At Purpose Financial we are always on the lookout for motivated individuals who share in our values of mutual respect to join our team of outstanding professionals.

We offer:

• Competitive Wages
• Health/Life Benefits
• Health Savings Account plus Employer Seed
• 401(k) Savings Plan with Company Match
• 3 Weeks of Paid Parental Leave
• 11 Company Paid Holiday's
• Paid Time Off including Volunteer Time
• Vacation Carryover
• Tuition Reimbursement
• Work-Life Balance
• Business Casual Environment
• Rewards & Recognition Program
• Employee Assistance Program
• Office in downtown Greenville that offers free parking, onsite gym, free snacks/drinks (for those working onsite or hybrid)

To learn more about Purpose Financial visit Purpose Financial Website.

 

Position Summary

The job function is responsible for building a scalable data infrastructure. This role reports to the Director of Decision Services in the data science team but works very closely with the enterprise data team to support the data science team and enable Purpose Financial to democratize data by developing self-service capabilities. The job function includes understanding of business requirements, defining data requirements, identifying enterprise data sources, planning, designing, and building data acquisition from sources, defining data model, designing data ingestion pipelines, data normalization, data transformation, and consumption using platforms such as Snowflake and AWS.

Job Responsibility

• Take ownership of building/optimizing data pipelines to increase efficiency and performance
• Support the data science teams data/model needs (i.e. real time ingestion into the decision engine of model input variables, storage of outputs, and data created in the data science team)
• Develop and maintain data ingestion and integration processes that focus on data quality and monitoring
• Use AWS and Snowflake tools such as Glue, Lambda, Matillion and Snowpipe to build data ingestion pipelines from various sources
• Partner with enterprise data, data scientists, and architects to adhere to enterprise standards and solutions
• Incorporate standards and best practices into data pipeline solutions

Job Responsibilities Cont.

• Participate in troubleshooting and problem-solving design discussions
• Provide logical and physical data design, and database modeling
• Solve complex data issues around data integration, unusable data elements, unstructured data sets, and other data processing incidents
• Apply best practices for AWS & Snowflake architecture, ELT and data models
• Act as SME for the data science team for database related topics, and assist with development of data lakes and warehouses

Education Required

Bachelor’s degree (or foreign equivalent degree) in any Computer, Engineering, or other technical field and 5+ years of experience.

Experience Required

• 4+ years experience in data warehousing
• 2+ years of experience in data architecture and design, with a good understanding of various data systems and structures (i.e. SQL, NoSQL, Key-Value, Streams)
• 2+ years of experience with building data pipelines and using data orchestration tools and implementing end to end Monitoring & Alerting solutions
• 2+ years of experience working with AWS or public cloud provider.
• Strong understanding of SQL, data structures, data integrity, and schema design best practices
• Programming experience required, preferably Python.
• A strong advocate of data governance and data quality
• Ability to drive a project from inception to completion
• Experience with database internals, database design, SQL and database programming
• Experience in financial services (Banking and consumer lending preferred)
• Experience of authoring CI/CD pipelines, automation elements related to infrastructure composition, deployment orchestration, and monitoring.