Verdata is a commercial data and analytics network that empowers trusted business
transactions across multiple end markets such as merchant acquisition, vertical SaaS, point of
sale finance, SMB lending, commercial insurance and more (www.Verdata.com). Verdata
supports US clients in onboarding clients in an automated and accurate manner as well as
monitoring client portfolios on a continuous basis for relevant material changes. Verdata's
rapidly growing 18+ million record proprietary commercial data network enables predictive
commercial risk scores for market specific use cases.
T echnology is the core of Verdata’s business, and we are looking for a Data Engineer with
Amazon EMR, Amazon Glue, Python, and Spark experience to join our growing product
development team. Reporting to the VP of Product Development, this role will work on
designing, building, and maintaining the data pipelines supporting our applications and APIs.
This role will work closely with internal and external partners to ensure the successful delivery of
Verdata’s product roadmap, data science efforts, data security certifications, and customer
commitments. This role requires ingenuity in finding quick solutions to problems with a bias
toward results and an eye toward long-term success. The Data Engineer also plays an auxiliary
role as an expert consultant to internal stakeholders who seek technical staff guidance and best
practices.
A day in the life…
● Drive and shape data pipeline development and maintenance for the Verdata platform
● Support, maintain, and grow the automation infrastructure that drives Verdata’s data
pipeline
● Design and support systems for delivering consistent, high-quality data for use in data
science efforts and customer-facing applications
● Develop a deep understanding of the existing data model to identify and implement
improvements in scalability, maintainability, availability, and data quality
● Support data security initiatives, including data permissions, data transmission, and
supporting SOC 2 certification activities
● Own projects end-to-end, from developing prototypes to ensuring reliable deployments
● Follow best practices to build easy-to-maintain, high-performing applications
● Collaborate with product development, product management, sales, and leadership to
deliver highly available, highly-scalable data systems
Qualifications
● Experience architecting and maintaining data pipelines, including extraction,
transformation, and loading (ETL)
● Experience with data pipeline technologies, including Python, Airflow, Apache Spark,
Amazon Elastic Map Reduce, and Amazon Glue (5+ years)● Experience supporting and scaling SQL databases in RDS (PostgreSQL and/or Amazon
Aurora are a plus)
● Experience working with data science technologies and techniques, including Anaconda,
Jupyter Notebook, SageMaker, machine learning models, and data attribute creation are
a plus
● Experience building and supporting AWS data security initiatives; experience with
helping organizations through security audits, including SOC 2, is a plus
● Entrepreneurial spirit and enjoys moving quickly on new, green-field products
● Has the ability to think deeply about data engineering. We care much more about your
general engineering skill than knowledge of particular packages or frameworks
● Communicate clearly and effectively with operations, marketing, executive leadership,
and the rest of the team
● Comfortability working as a team member of an early-stage startup is essential;
experience working at an early-stage startup is a plus
● Experience in the fintech or lending space is a plus
● Experience working with data science teams is a plus
● Diverse and driven individuals who want to make small business lending an amazing experience
Benefits
●We offer flexible vacation and sick leave policies
●Comprehensive healthcare, vision, and dental plans for you and your family
●Invest in your future with our 401K retirement plan
●Own equity in an exciting early stage growth company