Who We Are

Cross River is a highly profitable, fast-growing financial technology company powering the future of financial services. Our comprehensive suite of innovative and scalable embedded payments, cards, and lending products deliver financial services for millions of businesses and consumers around the globe. Cross River is backed by leading investors and serves the world’s most essential fintech and technology companies. Together with its partners, Cross River is reshaping global finance and financial inclusion. 

We are on a mission to build the infrastructure that propels access, inclusion, and the democratization of financial services. While our company has tripled in size over the last three years, our strong sense of purpose led Cross River to be named to American Banker’s list of Best Places to Work in Fintech for the last 6 years. The reason for this success is simple – our nimble, and collaborative family culture lives in every member of our growing team. Together we are at the forefront of technology and innovation, and we invite passionate, collaborative, and motivated, high performers to join our expanding team.

What We’re Looking For

The Data and Analytics team builds and operates systems to centralize all of the organization’s internal and third-party data, making it easy for teams across the company to access, process, and transform that data for analytics, and powering end-user experiences. As an engineer on the team you will contribute to the full spectrum of our systems, from managing foundational processing and data storage, to building and maintaining scalable pipelines, to developing frameworks, tools, and internal applications to make that data easily and efficiently available to other teams and systems. As such, you will play a key role in orchestrating and automating the data ingestion pipeline to make it more flexible while maintaining a high level of quality. The ideal candidate will have worked in a data engineering or science role, preferably at an investment bank or at a fintech and will have a basic understanding of consumer credit and related securitized products. You must have a strong sense of ownership, passion for technology and automation, self-starter, and thrive in a fast paced, unstructured startup environment.

Responsibilities:

• Design, build, and operate our foundational data infrastructure: storage (cloud data warehouse, S3 data lake), orchestration (Airflow), processing (Spark, Flink), streaming services (Kafka), BI tools (Tableau), graph databases, and real-time event aggregation stores.
• Design and build services for end-to-end data security and data governance: managing access controls across multiple storage and access layers, tracking data quality, cataloging datasets and their lineage, usage auditing
• Implement new features in our high-volume, in-house analytics service, and work closely with our customers to understand and solve their various use
• Manage Redshift/EMR infrastructure, and drive architectural plans and implementation for future data storage, reporting, and analytic solutions
• Write, test and review microbatch or streaming ETL powered by Kafka or AWS Kinesis
• Leverage your Python, Airflow, and AWS expertise to scale our Airflow data pipelines to the next 10x level.
• Lead, mentor, and coach junior data engineers

Qualifications:

• 8+ years of experience working as a Data Engineer role supporting ETL data pipelines and workflow orchestration tools (eg. Airflow)
• 5+ years experience working on batch and streaming data applications (Spark, Hadoop, Kafka, Kinesis, and Flink)
• You enjoy working with dynamic programming languages, relational databases, and distributed systems. Our platform is ever-evolving, but is a combination of Python, Scala, Postgres, Kubernetes, Spark, Cassandra, Kafka, and MongoDB
• Strong analytical and technical skills to troubleshoot issues, analyze the cause, quickly come-up with the possible solutions, document the changes, and communicate organizational impact
• Demonstrate sense of urgency in maintaining data integrity and experience automating recurring analyses
• Proactively seek to automate data operations and collaborate with cross functional teams to improve processes
• Excellent verbal communication skills and attention to detail
• Excited to learn new technologies and data transformation/analysis in general

Bonus:

• Interested in learning more about consumer lending analytics and the general finance domain
• Working knowledge of corporate banking and capital market products

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Salary Range: $140,000.00 - $160,000.00