Engineering Manager, Data Platform
Leads and remains hands-on with a 5–6-person team building data platform, ML infrastructure, and underwriting systems that power capital offers. Requires 5+ years of software engineering experience, technical leadership or management experience, and expertise in modern data and cloud infrastructure.
About the job
Responsibilities
- Manage and grow a team of 5–6 engineers across data storage and schema, feature store and ML platform, and underwriting platform.
- Lead hiring, mentorship, career development, and team culture.
- Set technical direction and drive execution across warehouse and data infrastructure, ML development lifecycle, and underwriting pipelines.
- Review designs and code, unblock complex technical issues, and personally lead architecture for high-priority initiatives.
- Own reliability and on-call processes, including incident response, SLAs, and recoverability.
- Partner with underwriting data science and product engineering teams.
- Represent roadmap priorities and technical tradeoffs to data science, merchant decisioning, product, and risk stakeholders.
Requirements
- 5+ years of software engineering experience, including 2+ years in technical leadership or engineering management.
- Experience in data infrastructure, ML platforms, or a related backend/data domain.
- Ability to remain close to execution and evaluate technical designs and tradeoffs.
- Strong understanding of modern data and lakehouse stacks, including Spark/PySpark, Databricks, Airflow, and AWS.
- Experience with feature stores, model training and serving pipelines, model registries, and batch and real-time inference.
- Experience managing engineers with empathy, providing direct feedback, and building high-ownership teams.
- Experience hiring strong engineers and supporting their career growth.
- Strong judgment in ambiguous, multi-domain environments, with emphasis on reliability and operational rigor.
- Excellent written and verbal communication skills, including communicating technical tradeoffs to technical and non-technical stakeholders.
Nice to Have
- Experience with the Databricks ecosystem.
- Startup experience.
- Fintech experience.
Compensation and Benefits
- Salary range: $290,000–$330,000.
- Equity grant.
- Medical, dental, and vision insurance.
- Work-from-home flexibility.
- Unlimited paid time off.
- Commuter benefits.
- Free lunches.
- Paid parental leave.
- 401(k).
- Employee assistance program.
Skills
Spark, Pyspark, Databricks, Apache Airflow, AWS, dbt, Feature Stores, Model Training, Model Serving, Model Registries, Batch Inference, Real-Time Inference, Data Warehousing, Incident Response
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