Engineering Manager, Data Platform

About Us:

At Parafin were on a mission to grow small businesses.

Small businesses are the backbone of our economy but traditional banks often dont have their backs. We build tech that makes it simple for small businesses to access the financial tools they need through the platforms they already sell on.

We partner with companies like DoorDash Amazon Worldpay and Mindbody to offer fast and flexible funding spend management and savings tools to their small business users via a simple integration. Parafin takes on all the complexity of capital markets underwriting servicing compliance and customer service for our partners.

Were a tight-knit team of innovators hailing from Stripe Square Plaid Coinbase Robinhood CERN and more all united by a passion for building tools that help small businesses succeed. Parafin is backed by prominent venture capitalists including GIC Notable Capital Redpoint Ventures Ribbit Capital and Thrive Capital. Parafin is a Series C company and we have raised more than $194M in equity and $340M in debt facilities.

Join us in creating a future where every small business has the financial tools they need.

The Data Platform team owns the systems that generate every capital product offer at Parafin powering both batch and real-time underwriting across all of our partners and products.

Were looking for an engineering manager who is still deeply technical closer to a tech lead manager. Youll set technical direction for the team and manage and grow a team of 5-6 engineers across three tightly coupled areas: Data Platform (warehouse ingestion Airflow/Databricks infra) Feature Store & ML Platform (feature materialization model training/serving lifecycle) and Underwriting Platform (batch and real-time pipelines that generate offers).

This is a high-leverage role: every improvement to platform reliability or iteration speed compounds across 60 partners and every product line. Youll also be a primary technical partner to Underwriting Data Science that owns model research risk analysis and new product development as well as to product engineering teams that build features on top of the data and underwriting systems this team owns.

• Manage and grow a team of 5-6 engineers spanning Data storage and schema Feature Store/ML Platform and Underwriting Platform including hiring mentorship and career development.

• Set and drive execution and technical strategy for the teams three areas: warehouse/data infrastructure (Databricks Airflow dbt) the feature store and ML dev lifecycle (feature materialization training batch/real-time inference model registry) and underwriting pipelines (nightly batch underwriter real-time Kitchen RTU).

• Stay hands-on: review designs and code unblock the team on hard technical problems and personally drive architecture on the highest-priority initiatives.

• Own reliability and on-call for the teams systems; build sustainable processes around incident response SLAs and recoverability

• Partner closely with underwriting data science and product engineering teams that build on top of the data platform

• Represent the teams roadmap and tradeoffs to cross-functional stakeholders (DS Merchant Decisioning Product Risk) and prioritize across data infra ML platform and underwriting pipeline needs.

• 5 years of software engineering experience including 2 years in a technical leadership or engineering management role ideally in data infrastructure ML platform or a similar backend/data domain.

• Ability to stay close to the teams execution review/discuss technical designs and trade-offs

• Strong understanding of modern data/lakehouse stacks: Spark/PySpark Databricks Airflow and cloud infra (AWS).

• Experience with ML infrastructure concepts: feature stores model training/serving pipelines model registries batch and real-time inference.

• Track record of managing engineers with empathy giving direct feedback and building a healthy high-ownership team culture.

• Experience building strong teams by hiring to a high technical bar and actively growing engineers careers.

• Experience navigating ambiguity and competing priorities across multiple technical domains and stakeholders; strong judgment around reliability and operational rigor

• Excellent written and verbal communication; comfortable representing technical tradeoffs to both engineers and non-technical stakeholders.

• Experience with Databricks tech ecosystem

• Experience at startups

• Experience in the fintech domain

• Salary Range: $290k - $330k

• Equity grant

• Medical dental & vision insurance

• Work from home flexibility

• Unlimited PTO

• Commuter benefits

• Free lunches

• Paid parental leave

• 401(k)

• Employee assistance program

If you require reasonable accommodation in completing this application interviewing completing any pre-employment testing or otherwise participating in the employee selection process please contact us.

Required Experience:

Manager