Who We Are: 

Ocrolus is a fintech infrastructure company that transforms documents into actionable data. Powered by Artificial Intelligence and a unique human-in-the-loop data validation process, Ocrolus plugs directly into customer workflows via API, eliminating the need for manual data work. The solution includes built-in fraud detection and analytics, enabling customers to make smarter and faster business decisions with unprecedented precision.

Use-cases include loan underwriting, account openings, invoice processing, and other document-intensive processes. Ocrolus has raised over $30 million in venture capital, backed by Oak HC/FT, FinTech Collective, Bullpen Capital, and QED Investors, among others.

We are seeking a candidate with proven experience building data intensive systems to join our Data Team as a data centric architect, engineer, and technical leader.

Data Engineering at Ocrolus:

Ocrolus is a fast growing company with many emerging data needs. We are establishing new platforms and capabilities for users both inside and outside of the company. We are building to support a wide variety of use cases with a high degree of engineering rigor as well as product agility. We value engineering excellence, automation and testing and believe doing these things well will create more long term value than simply shipping new features fast.

Responsibilities:

• This is an engineering centric role: Domain expertise in data systems and databases must be balanced with the ability to implement!
• Help our Data Platform team develop a single, generalized real-time data pipeline that assures all company and client data is handled consistently
• Develop a framework for managing schemas and for handling schema evolution across our platform
• Enable democratized data quality and analytics over our data sources Translate our data governance strategy and policies in a single shared implementation that is both user friendly and risk averse
• Establish a comprehensive set of data models for company and client data
• Partner with Product and Machine Learning Engineers to optimize our data collections and minimize the amount of reverse engineering is needed within our data pipelines
• Make sure our user facing databases are performing well and serving the needs of our organization and clients

Requirements:

• 5+ years experience working on data warehousing, data systems, machine learning, or big data problems 
• 5+ years of software engineering experience using python, scala, java, c++, etc
• Significant experience as a technical lead for previous data warehouse, data lake, or other distributed data system implementations
• Demonstrated understanding of the data needs of a machine learning centric engineering organization. 
• Able to translate company strategy into needs, requirements and action. Able to drive company wide consensus on how we model our most valuable data assets
• Advanced physical data modeling, indexing, and database tuning knowledge (scaling both reads and writes)
• Bachelors in Computer Science or related field

Extra Credit

• Experience thoughtfully implementing security standards such as PCI or SOC 
• Significant Data Modeling experience
• Advanced degree, PHD or Masters in Computer Science or related field

We’re a young and rapidly growing FinTech company - if you have ever wanted to jump on a rocket ship as it’s taking off, now is your chance!