Sitting at the intersection of our Data Science and Data Extraction engineering teams, the Data Wrangler position focuses on ETL (“Extract, Transform, Load”) tasks involving large data sets from a variety of sources. You will manage the infrastructure and code base that processes data relating to millions of financial accounts each day. A true “Big Data” role, you will manage both system architecture and the specific code that manages these important processes.

About Us: Quovo is the leading provider of account aggregation and data analytics technology for finance. Hundreds of financial institutions, advisors, and fintech companies utilize Quovo technology as the foundation for their service offerings, aggregating and integrating millions of daily transactions. Our office is located in the heart of Manhattan and we offer a full range of benefits including health, vision, dental, 401(k), and commuter benefits.

Responsibilities:

• Manage and monitor large-scale ETL processes for financial account data.
• Build and enhance the ETL codebase for added efficiency and capacity.
• Work with the Data Extraction and Data Science engineers on normalization and analytics processes.
• Monitor key infrastructure components such as databases, SFTP servers, and other parts of the stack.

Skills and Experience:

• Experience with ETL and/or other “Big Data” processes.
• Experience coding in Python (ideally in the context of data processing or data science).
• Strong SQL experience, ideally with MSSQL or PostgreSQL and batch loading processes.
• 5+ years of engineering experience in a professional environment, but skill fit is a higher priority to us than just work experience.
• B.S. or M.S. in Computer Science, or equivalent work experience.
• Excellent communication and collaboration skills. Able to work across multiple teams and discuss technical concepts to business development, operations, and other engineers.