Data Engineer II

Role overview A digital financial platform focused on serving underbanked consumers is hiring a Data Engineer II to strengthen the data infrastructure that powers product, risk, analytics, and operational decisions. The role sits within the data engineering team and partners closely with analytics, data science, finance, risk, marketing, product, and engineering groups. It is hands-on production work with growing ownership of pipelines, modeling, and platform reliability.

Responsibilities - Build, maintain, and improve reliable data pipelines that ingest, transform, and deliver data across a modern data platform. - Own data engineering projects from implementation and testing through deployment, monitoring, troubleshooting, and ongoing support. - Work with Snowflake, dbt, Airflow or Cloud Composer, APIs, file sources, and cloud services to optimize workloads for reliability, performance, scalability, and cost. - Contribute to warehouse development through schema design, data modeling, testing, documentation, data quality practices, and query optimization. - Improve ingestion, orchestration, validation, retries, backfills, monitoring, and alerting while reducing recurring operational toil. - Use AI-assisted development tools thoughtfully to accelerate coding, debugging, documentation, and analysis without compromising accuracy, security, or review standards.

Requirements - 2+ years of software or data engineering experience, including time building or supporting production data systems. - Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience. - Strong programming skills in Python, Java, or another general-purpose language, plus strong SQL skills. - Hands-on experience building or maintaining ETL or ELT pipelines with tools such as dbt, Fivetran, or equivalents. - Experience with cloud data warehouses such as Snowflake, BigQuery, or Redshift, and orchestration tools such as Airflow or Cloud Composer. - Solid grasp of data modeling, data quality, relational data, and query and performance optimization, plus core software engineering fundamentals such as version control, testing, code reviews, and CI/CD.

Nice to have - Experience with financial or other highly regulated datasets. - Familiarity with GCP services such as Dataflow and Pub/Sub.

Benefits and work setup - Reports to a Data Engineering Manager with meaningful ownership supported by senior engineers. - Remote-first culture within the United States (excluding Hawaii), with flexible hours and a home office stipend. - Premium medical, dental, and vision insurance, generous paid parental and caregiver leave, and a 401(k) with matching contributions. - Financial advisor and financial wellness support, flexible PTO, generous company holidays, and periodic in-person and virtual team events.