Who we are

PeerIQ is transforming the way lending and securitization markets work. We work with industry leaders to unlock capital at scale, meeting the needs across the credit funding cycle: from loan purchasing to financing to securitization. We aim to bridge the gap between originators and the capital markets so that investors can invest with confidence. Our employees come from the technology and financial sectors, combining the best both to change the game of consumer credit.

PeerIQ was acquired by CRB Group, Inc in June 2021 and is an affiliate of Cross River. Together, we are on a mission to build the infrastructure that propels access, inclusion, and the democratization of financial services.

Cross River is a highly profitable fast-growing financial technology company recognized for the third year in a row by CB Insights as one of the 250 best global fintechs. Our comprehensive suite of innovative products powers financial solutions with a strong focus on regulatory compliance for our partners and their millions of consumers around the world.

What we're looking for
The Data and Analytics team builds and operates systems to centralize all of PeerIQ'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

Salary Range: $140,000 - $160,000

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