Join the Ocrolus rocket ship!
Ocrolus is a fintech infrastructure company that transforms documents into actionable data with over 99% accuracy. Designed to streamline document-driven workflows and automate high-stakes financial decisions, Ocrolus is trusted by leading fintechs like SoFi, LendingClub, Cross River Bank, BlueVine, Enova, and Plaid, to name a few. 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. Ocrolus has raised over $50 million in venture capital, backed by Oak HC/FT, FinTech Collective, Bullpen Capital, and QED Investors, among others.
We pride ourselves on being a dynamic, diverse team, unified by shared values of Ownership, Optimism, Objectivity, Humility, Urgency, and Appreciation. We love what we do and the people we do it with, which is why we invite our team to bring their full selves to work every day.
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.
- Build Python data producers and consumer for Kafka
- Help our Data Platform team develop a single, generalized real-time data pipeline that assures all data is handled consistently utilizing Kafka Connectors to ingest/sink data (Apache Debezium, Snowflake Sink, etc)
- Build Java Kafka-Streams (KStreams) Applications to create data pipelines in Kafka
- Develop and evolve both Avro schemas (AVSC) in the schema registry, and relational database schemas in PostGres and Snowflake to manage our data as it moves through the platform
- Partner with Product and Data Science to build new client facing analytics and internal tools making Ocrolus more data driven
- Participate in the design and implementation of best practices in our kafka cluster(s), applications, and other data infrastructure
- Maintain, automate, and optimize reporting infrastructure, including cleaning, enriching, and restructuring datasets
- Bachelor's in Computer Science or related field required
- 5+ years experience working on data warehousing, data systems, machine learning, or big data problems
- Analytical and Business Intelligence/visualization skills a plus
- 5+ years of Data Engineering or Software Engineering experience using Python, Scala, Java, etc
- Fluent in Python and Java
- KStreams Application experience is a plus
- Fluent in advanced SQL (DDL & DML): data modeling, indexing, and database tuning
- Experience with data warehouses, data lakes or other distributed data system implementations
- Postgres, RedShift, Snowflake, Avro experience is a plus
- Strong communication skills and experience communicating across business units
- Experience working with Data Scientists and Data Analysts is a plus
- Ability to create fast solutions to problems introduced in a changing environment with iteration towards optimal solutions
- Scrum Agile team experience
Our employees are incredible individuals - that’s the only kind we hire - and we’re committed to their well-being and supporting their efforts to become the best they can be, both at work and in life. This includes offering flexible working hours, unlimited PTO, Summer Fridays, an inclusive work environment (D&I Council), and wellness reimbursement for physical and mental well-being.
We’re growing rapidly and were recently named #1 Fastest-Growing Fintech Company on the Inc. 5000, and #1 Fastest-Growing Software Company in NY in Deloitte’s Technology Fast 500. If you have ever wanted to jump on a rocket ship as it’s taking off, now is your chance!
Ocrolus is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.