Senior Data Engineer

GlobalRemote

Responsibilities

- Design and extend multi-tenant data architectures to support a scalable SaaS model.
- Lead and execute infrastructure migrations with minimal downtime and high data integrity.
- Build and maintain custom ingestion pipelines for data sources not covered by ELT vendors.
Observability, Performance & Maintenance - Build or integrate observability tooling for pipeline health, latency, data freshness, drift detection, and schema change monitoring.
- Drive a culture of data reliability engineering by codifying best practices, automation, and operational excellence.

By unifying processes into a modern, AI-native operating system, we’re leading the way in automation, compliance, and continuous improvement across our servicing and lending businesses.
experience successfully creating/optimizing/scaling data stacks and supporting data teams, at least 2 years in an early- to mid-stage startup - Deep knowledge and
experience deploying and optimizing dbt or comparable tooling -
Experience managing multiple types of data management systems (data warehouses, data marts, data lakes) -
Experience building/procuring tools and processes to monitor end-to-end data stack health - Mastery of SQL from both functionality and performance perspective - Fluency in writing scripts in Python or a similar language -
Experience working with and tuning cloud data warehouses and compute environments.
Experience with BigQuery/GCP a plus -
Experience managing/tuning EL connector solutions (such as Fivetran, Stitch, etc.) and building custom ingestion pipelines - Strong prioritization skills, effort vs. impact thinking, stakeholder management - Ability to reason about factors/interactions/root causes outcomes across the data stack, able to back up arguments/decisions with data - Deep understanding of data team workstreams and needs, ideally in the form of past
experience as a data analyst/data scientist