Lead Data Engineer

Current Employees of Happen Bank: Please apply via your internal Workday Account

Happen Bank (formerly LendingClub) 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.

About the Role

Happen Bank's Data Operations Center ensures consistent, reliable delivery of data that powers critical business functions across finance, accounting, investor reporting, and collections. As a Lead Data Engineer, you'll lead the Financial Data Operations team, owning the pipelines that support month-end close, investor servicing, revenue recognition, and other high-impact processes that keep the business running smoothly. You'll act as the bridge between engineering, product, and business stakeholders while building team capability and driving operational excellence through smart automation and AI-driven improvements.

What You'll Do

Lead a cross-functional scrum team of onshore and offshore data engineers, setting priorities and removing blockers to deliver reliable data products

Own the architecture, maintenance, and continuous improvement of critical financial data pipelines that support GL automation, investor reporting, tax documents, and collections workflows

Partner with finance, accounting, and operations stakeholders to translate business requirements into scalable technical solutions

Drive adoption of modern data platform capabilities, including Databricks, dbt, Elementary, and Dagster, while maintaining existing production systems

Identify opportunities to leverage AI tools for QA automation, code review, performance optimization, and documentation standardization

Build and improve monitoring, alerting, and observability practices to ensure pipeline reliability and rapid incident response

Establish coding standards and data quality frameworks that scale across the team and reduce operational overhead

Use AI to create intelligent runbooks, diagnostic agents, and self-service tools that empower L1 support and accelerate troubleshooting

About You

8+ years of experience in data engineering, with 2+ years leading teams or projects in a technical lead capacity; bachelor's degree in a related field; or equivalent work experience

You have hands-on experience using AI tools to accelerate your work and improve output quality - you're equally comfortable using them yourself and showing colleagues how, and you're thoughtful about limitations and where human judgment matters most

Strong expertise in SQL, data modeling, data warehouse concepts, and building production data pipelines at scale

Experience with orchestration tools such as Airflow, Oozie, or Dagster and distributed processing frameworks like Spark or PySpark

Working knowledge of AWS services (EMR, S3, Redshift) and modern data platforms such as Snowflake or Databricks

You take ownership of outcomes, proactively identifying risks and workflow improvements before they become blockers

Strong communication and organizational skills with experience collaborating across business, product, and engineering teams

Experience leading or mentoring offshore engineering teams and managing work across time zones

You balance technical depth with business context, understanding how data pipelines support financial processes and regulatory requirements

Nice to Have

Experience with dbt for data transformation and Elementary for data validation

Hands-on use of AI tools such as Claude, ChatGPT, or GitHub Copilot to improve development workflows

Background in financial services, accounting systems, or investor reporting processes

Experience building self-service analytics tools using Streamlit or similar frameworks

Familiarity with data quality frameworks, alerting systems, and SRE practices for data infrastructure

Work Location

San Francisco

The above locations are eligible offices for this role. The locations have been determined to foster in-person collaboration with this role’s team or the related business lines. We utilize a hybrid work model, and our teams are in-office Tuesdays, Wednesdays, and Thursdays. In-person attendance is essential for this role’s success, and remote placement will not be considered. Happen Bank offers relocation, based on actual job level.

Time Zone Requirements

Local hours (PT)

While the position will primarily work local hours, Happen Bank is headquartered in Pacific Time and our ideal candidate will be flexible working across time zones when necessary.

Travel Requirements

As needed travel to Happen Bank offices and/or other locations, as needed.

Compensation

The target base salary range for this position is 190,000-220,000. The base salary of the role will be determined by job-related knowledge, experience, education, skills, and location. Base salary is just one part of Happen Bank's Total Rewards package. You may also be eligible for long-term awards (equity) and an annual bonus (which is based on company performance, employee performance and eligible earnings).

We’re creating new financial services solutions for our members based on fairness, simplicity, and heart, and we treat our employees the same way. We offer a competitive benefits package that includes medical, dental and vision plans for employees and their families, 401(k) match, health and wellness programs, flexible time off policies for salaried employees, up to 16 weeks paid parental leave and more.

#LI-Hybrid

#LI-JH1

We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application process. If you need assistance or an accommodation due to a disability, please contact us at interviewaccommodations@happen.com.

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