About the Role
We’re looking for an experienced Data Engineering leader that focuses on data engineering best practices, architecture, processes to help build reliable, performant, and scalable data platforms. This person will be crucial to the success of our company, report directly to the CEO, define the future of Data Engineering at Miren, with a deep focus on data quality, velocity, and curation.
What You'll Also Do
Collaborate with the CEO and leadership team on deals, product roadmap, and our go-to-market strategy
Design and develop a data platform to support machine learning and analytics.
Architect and deploy scalable infrastructure, pipelines, and integrations.
Create company wide system architecture and design with the above in mind.
Stay on top of technological developments for data ingestion, processing, and serving.
Set standards and best practices with regards to methodologies and tools
What You'll Need
You have 3+ years of experience with relational databases and SQL as a language. Postgres experience is preferred.
3+ years of building and launching new data models that provide intuitive analytics.
3+ years of developing and deploying scalable database solutions and pipelines.
Production grade coding proficiency in Python and its ecosystem i.e. pandas, numpy, etc.
Demonstrated experience in containerization & orchestration with Docker & Kubernetes (EKS/AKS/GKE).
Experience with version control software e.g. GIT
Technologies We Use
docker (ECS and EKS)
Bonus Points if You Have . . .
Masters Degree in Computer Science or related field.
Experience working in or with Data Science or Machine Learning oriented teams and organizations.
Have worked with AWS services and products e.g. DMS, CFN, etc.
Experience with Redshift or other columnar data stores
Experience in working with financial institutions
Seed and/or Series A start-up experience
About the Company
Miren expands access to financing capital by enabling financial institutions, big and small, to better assess the risk profiles of no-credit and credit-thin small business owners with our software and data services. We want to build a world in which there is no use for credit scores in small business lending.
For community development financial institutions (CDFIs) and credit unions, we build software to enable teams to optimize their loan intake and portfolio management processes without impacting their manual underwriting. For community banks, we provide an enrichment data layer so that they can use alternative data, instead of traditional credit scores, in their underwriting models.
For community development financial institutions (CDFIs) and credit unions, we build software to enable teams to optimize their loan intake and management processes without impacting their manual underwriting. For community banks, we provide risk data sets so that they can use alternative data, instead of traditional credit scores, in their underwriting models.