Fin’s Backend Engineer Role

The core of Fin’s data platform is, in essence, one big data transformation pipeline. It ingests user activity events (both real-time from the browser, and periodically from external APIs), transforms the data to represent workflows and behaviors, and ultimately presents the data and insights as interactive visualizations to our customers.

Unlike other analytics platforms that offer basic free-form exploration, Fin’s data models are quite opinionated about what constitutes work. This approach dramatically reduces the time required for customers to get value from Fin.

As Fin undergoes significant user growth, we must continue to build scalable and performant data processing systems and infrastructure. Accordingly, Fin seeks a backend engineer to join our team and help us build a petabyte-scale data platform.

The Ideal Fit

• You have spent 5+ years building large-scale data systems (or equivalent experience) and have driven their growth and maturation over time.
• You have strong experience using Python to develop backend applications that efficiently process data and move data in/out of relational databases or similar data repositories such as file systems, data warehouses or NoSQL databases.
• You are capable of defining and creating data models needed for your applications and writing effective SQL statements in client applications to read/write data from those models.
• You can effectively communicate with, and efficiently build consensus among, enthusiastic and talented peers in an ambiguous problem space.
• You can effectively collaborate across teams & functions (e.g.: marketing, sales, solutions, product management, etc.) and provide meaningful input into product direction.
• You can own the entire lifecycle of building features, including scoping, design, implementation, and testing.
• You have significant experience with developing applications and optimizing efficiency and costs using AWS technologies (Aurora, Kinesis, Redshift, Athena, Glue, etc.).
• You are comfortable working in an early-stage startup environment: building and shipping frequently, willing to take risks, iterating quickly as we learn from customers using our products, and helping to shape the engineering culture.

Nice-to-haves

• Experience with some database administration such as backups, restores, user/role security, access permissions and query optimization.
• Experience with ETL tools such as Upsolver, Fivetran, Datacoral, etc.
• Familiarity with Docker, Kubernetes and microservice based architecture.
• Familiarity with data streaming architectures and software such as Kafka, Striim, Databricks, ElasticSearch, Druid, etc.
• Familiarity with the customer operations (”CX”) domain and tools (Salesforce, Zendesk).