About the Role
Figure is excited to be growing our businesses and creating new teams. We are looking for curious, innovative and collaborative team members. Engineering is at the heart of the action, building out our blockchain protocol and direct to consumer products that will transform the financial services industry. Everything is from scratch development and every engineer has a big impact on the team and the growth of the company.
As part of our Data Engineering team, you’ll work closely with various business functions to understand Figure’s analytic, data science, and reporting needs and to develop data products that address those needs. You will be contributing to data engineering’s vision and development from day one.
This team has an incredible engineering challenge: integrate very large datasets that outline intricate details about consumers’ credit profiles and real estate holdings, expose those datasets to data scientists in a way that enables their ML and modeling efforts, and shape those models into scalable, production-quality processes. In addition, the team provides the foundations for internal analytics and for internal and external reporting by transforming data from Figure applications and external vendors into clear data models.
What You’ll Do
- Leverage Spark, Airflow, Google Kubernetes Engine, BigQuery and other tools to build robust and efficient data pipelines.
- Expand and optimize our data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams.
- Collaborate with project leads and other software engineers across multiple teams
- Work on data software solutions that will transform the consumer lending and blockchain space
- Be a leader, use your voice, apply your tech skills to solve real world problems
What We Look For
- BS degree in Computer Science or related technical field, or equivalent practical experience.
- 6+ years of proven working experience as a data engineer
- 3+ years’ experience with Spark, either in Python or in Scala. Bonus points for Spark on EMR, Dataproc, or Kubernetes.
- Working knowledge of Google Cloud tools (compute, cloud storage, GKE, GCR, AutoML, etc.)
- Expertise building and optimizing data pipelines using Kafka (preferred), Kinesis, or other event bus.
- Deep experience with data frameworks and tools like Spark, SparkML, Spark Streaming, Apache Beam, and Airflow.
- Comfort with and experience working within CI/CD processes and tools and software development practices.
- Experience with production machine learning workflows and processes.
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of SQL and NoSQL databases, including BigQuery (preferable), MySQL/MariaDB, Postgres or Cassandra.
- Expertise in data modeling for data science, reporting, and analytics, including dimensional and transactional models.
- Nice to have: experience building real-time transformations and learning models on streams.
- Ability to thrive in a fast-paced growing company.
Benefits To You
- Competitive salary
- Firm-wide performance based bonus
- Competitive stock options package
- A flexible paid time off and vacation policy
- Comprehensive health, vision, dental insurance
- Company FSA, 401k, commuter benefits
- And much more to come!