Sr. Data Engineer

Purpose Financial•Greenville, SC

34d•Onsite

About The Position

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 800 storefronts locations and online lending. Providing services in over 23 states, Purpose Financial employs over 2,500 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. Purpose Financial is seeking a talented and motivated Sr Data Engineer to join our dynamic and growing data engineering Platform Team. The role reports to the Director, Data & Platform Engineering and will support Purpose Financials initiative build a data driven culture and improve decisioning for enterprise-wide teammates. Experience with dbt required. The Senior Data Engineer will play a pivotal role in designing, building, and maintaining our data infrastructure and pipelines to enable efficient collection, storage, processing, and analysis of large-scale datasets. Collaborate with cross-functional teams to build and acquire underlying data for application owners and end-users and design strategic data services for the organization. The right Senior Data Engineer will need to have expert knowledge of AWS and/or Snowflake cloud environments.

Requirements

10+ years of experience in data engineering, data pipelines, and data services required.
Familiarity with Agile/Scrum based development and methodology.
Strong proficiency in programming languages such as Python, SQL, Spark, or Java, with experience in data manipulation, transformation, and analysis.
Expert level experience with cloud-based data platforms and services such as AWS, Snowflake and dbt.
Experience with distributed computing frameworks such as Apache Spark, Kafka, etc.
Proficiency in database systems, data warehousing, data patterns/architectures, and SQL query optimizations.
Familiarity with containerization and orchestration technologies such as Docker or Kubernetes.
Excellent problem-solving skills, attention to detail, and ability to work effectively in a fast-paced and collaborative environment.
Strong communication, interpersonal and teamwork skills, with the ability to interact with stakeholders at all levels of the data team.
Excellent written and verbal communications skills; adaptability and flexibility to a changing environment; and comfortable working in a dynamic, high volume, fast-paced environment. Ability to understand and ensure compliance with policies, procedures, and laws governing our industry/business and products.
Sitting for long periods of time; standing occasionally; walking; bending; squatting; kneeling; pushing/pulling; reaching; twisting; frequent lifting of less than 10 lbs., occasional lifting of up to 20 lbs.; driving and having access during the workday to an insured and reliable transportation; typing; data entry; grasping; transferring items between hands and/or to another person or receptacle; use of office equipment to include computers; ability to travel to, be physically present at, and complete the physical requirements of the position at any assigned location.
Must be eligible to work in the USA and able to pass a background check.

Responsibilities

Design, develop, and maintain scalable and reliable data pipelines to ingest, transform, and load structured, semi-structured, and unstructured data from various sources into our data lake and warehouse environments.
Implement data integration solutions to consolidate data from disparate sources, including databases, API’s, streaming platforms, and 3rd party services (e.g., Snowpipe, SnowPark, Dynamo, Kafka).
Optimize data processing workflows for performance, efficiency, and scalability using distributed computing or parallel processing frameworks such as FiveTran, dbt, Snowpark, Snowpipe, etc.…
Collaborate cross-functionally with IT & business stakeholders to understand data requirements, define data models, and develop solutions to support data services, reporting, and Software Development.
Partner with data, IT, and business teams to improve design and building of metrics to enhance our analytic capabilities.
Implement data quality checks, data validation processes, and error handling mechanisms to ensure the accuracy, completeness, and reliability of data across all stages of the data lifecycle.
Support the design and maintenance of data schemas, and metadata repositories for governance documentation of data lineage, definitions, and dependencies.
Support the development and maintenance of data governance policies, standards, and best practices to ensure compliance with data privacy regulations and industry standards.
Apply best practices for AWS and Snowflake architectures, data pipelines and data models.
Monitor, troubleshoot, and optimize the performance and availability of data systems and infrastructure using monitoring and logging tools such as Prometheus.
Stay current with emerging technologies, tools, and trends in data engineering, cloud architectures, and cloud computing to evaluate their potential impact and relevance to our data platforms.
Responsible to coach and mentor junior data engineers.

Benefits

Competitive Wages
Health/Life Benefits
Health Savings Account plus Employer Seed
401(k) Savings Plan with Company Match
Paid Parental Leave
Company Paid Holidays
Paid Time Off including Volunteer Time
Tuition Reimbursement
Business Casual Environment
Rewards & Recognition Program
Employee Assistance Program
Office in downtown Greenville that offers free parking, onsite gym, free snacks/drinks