Principal Software Engineer, Data Infrastructure

Happen Bank (formerly Lending Club) is built around a simple purpose: to clear the way to help people turn intention into action, and action into financial progress. That means offering focused products, a frictionless mobile‑first experience, and clear terms with no gotchas. Respect and fairness is part of our DNA, and that ideal shapes how we work, how we treat each other, and how we invest in our employees and our community.

Join us in using data, bold thinking, and a commitment to innovation to help clear the way for millions of Americans to achieve more.

Happen Bank is building a modern enterprise data and AI platform on Databricks. Our Data Engineers, Data Scientists, and Analytics teams build the pipelines. This team builds what they build on. As a Principal Data Engineer, you'll own the technical architecture and development of the platform frameworks and infrastructure that make downstream pipelines faster, safer, and more consistent. This includes configuration‑driven ingestion frameworks, secure connectivity to source systems, reusable data protection libraries for anonymization and tokenization, and the infrastructure‑as‑code foundation that brings these capabilities together.

This is a framework and platform engineering role, not a pipeline‑delivery role. Success means enabling teams to onboard new data sources, protect sensitive information, and promote work to production through configuration rather than custom code.

• Own ingestion architecture:
  Define the technical vision and architecture for a declarative, configuration‑driven ingestion framework that brings data from relational databases and object‑store files into the raw data layer. Establish reusable patterns and contracts for downstream teams while evaluating tradeoffs between ingestion approaches.
• Build scalable platform frameworks:
  Lead the design and implementation of reusable, versioned libraries that support policy‑driven data protection, including configurable rules, governed access, consistent outputs, secure‑by‑default failure behavior, and audit trails. Maintain backward compatibility across shared capabilities used by multiple teams.
• Set infrastructure and deployment standards:
  Define infrastructure‑as‑code practices for safe deployment, replacement, rollback, and lifecycle management, including data ownership considerations for managed pipeline objects. Establish compute, cost, and sizing guidance for large initial loads and steady‑state incremental processing at billion‑row scale.
• Drive platform reliability and observability:
  Establish monitoring, alerting, reconciliation, recovery, and data validation capabilities that ensure reliable operations from source to destination. Identify and address observability gaps in underlying platform tools.
• Lead evidence‑based technology decisions:
  Conduct structured proofs of concept with measurable success criteria, document architectural decisions and tradeoffs, and engage technology vendors to resolve product gaps and influence future capabilities.
• Drive cross‑functional platform delivery:
  Translate ambiguous technical challenges into clear requirements, interfaces, dependencies, and phased delivery plans. Partner with Data Engineering, Data Governance, Information Security, DBAs, and source‑system owners to deliver early solutions while building scalable long‑term capabilities and driving framework adoption.
• Raise engineering standards:
  Mentor senior and staff engineers, lead technical design and code reviews, and establish best practices for testing, documentation, release management, and maintainability across shared platform capabilities.

• 10+ years of software or data platform engineering experience, including designing and…