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Principal Data Engineer

LendingClub

Principal Data Engineer

LendingClub

San Francisco, CA

·

On-site

·

Full-time

·

2w ago

Compensation

$198,000 - $230,000

Benefits & Perks

Healthcare

401(k)

Equity

Flexible Hours

Parental Leave

Healthcare

401k

Equity

Flexible Hours

Parental Leave

Required Skills

Python

Data engineering

Distributed systems

SQL

Machine learning

Current Employees of Lending Club: Please apply via your internal Workday Account

Lending Club Corporation (NYSE: LC) is the parent company of Lending Club Bank, National Association, Member FDIC. We are the leading digital marketplace bank in the U.S., having helped our nearly 5 million members secure over $90 billion in loans to refinance high-cost debt and achieve their financial goals. Members today have mobile-first access to a growing range of products and services designed to work seamlessly together to deliver value in new ways. Everyone deserves a better financial future, and our team is committed to making that a reality. Join the Club!

About the Role

Our mission at Lending Club is to empower those who strive to achieve better financial health. The Data and Analytics team plays a crucial role in achieving our mission.

We are seeking a Principal Data Engineer to lead the design and evolution of data systems that power batch processing, real-time streaming, pipeline orchestration, data lake management, data cataloging, and machine learning workflows. This role has a strong emphasis on enabling and scaling machine learning and analytics use cases, including feature engineering, model training, and inference data pipelines.

In this role, you will apply deep technical expertise, architectural thinking, and hands-on development to solve complex big data and ML platform challenges. You will partner closely with Data Science, Product, and Platform teams to build reliable, scalable, and cost-efficient data foundations that support both analytics and production machine learning systems.

What You'll Do

  • Design, build, and own large-scale data and ML data pipelines that integrate directly with Lending Club’s products and external vendors
  • Design and operate data platforms where autonomous coding agents help maintain pipelines, schemas, and tests, while you own architecture and guardrails.
  • Lead the architecture and implementation of MLOps including feature stores, training datasets, batch and real-time inference pipelines
  • Work with modern data technologies such as Hadoop, Spark, DBT, Dagster/Airflow, Atlan, and modern data platforms like Databricks and Snowflake, across the AWS cloud stack
  • Partner with Data Scientists to productionize ML workflows and ensure data reliability, reproducibility, and performance
  • Identify, design, and implement automation of manual processes, optimizing data delivery, improving system reliability, and reducing cloud costs
  • Implement processes and systems to monitor Data Quality, Observability, Governance, Lineage, and ML data consistency
  • Define policies, workflows, and quality gates for using AI agents in production data systems.
  • Provide technical leadership and mentorship, influencing data engineering standards, best practices, and long-term platform strategy
  • Coach teams on decomposing work, supervising agents, and validating AI-generated changes.
  • Support operations to manage the production environment and lead root cause analysis (RCA) for complex data and ML pipeline issues
  • Write unit and integration tests, advocate for test-driven development, contribute to engineering documentation and design reviews

About You

  • 8 years of data engineering experience with deep hands-on experience with distributed data systems including Hadoop, Spark, Hive, DBT, and Airflow/Dagster
  • Bachelor’s degree in computer science or a related field, or equivalent work experience
  • 5 years of production-quality Python experience, building and maintaining large-scale data pipelines
  • Strong experience building machine learning use cases through data engineering (e.g., feature engineering pipelines, training/inference data flows)
  • Experience working with public cloud platforms, preferably AWS
  • Experience with Databricks and/or Snowflake in production environments
  • Strong working knowledge of Git, JIRA, Jenkins, shell scripting
  • Familiarity with Agile methodologies, test-driven development, source control management, and test automation
  • Proven ability to work across cross-functional teams in a fast-paced, dynamic environment
  • Excellent collaborative problem-solving and communication skills, with the ability to influence without authority
  • A track record of designing and delivering scalable, reliable, and high-quality data platforms
  • Nice to have: experience building data pipelines for Digital Marketing use cases

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. Lending Club offers relocation, based on actual job level.

Time Zone Requirements

Primarily PT

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

Travel Requirements

As needed travel to Lending Club offices and/or other locations, as needed.

Compensation

The target base salary range for this position is 198,000-230,000. 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 Lending Club’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.

Lending Club is an equal opportunity employer and dedicated to diversity, equity, and inclusion in the workplace. We do not discriminate on the basis of race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), gender, gender identity, gender expression, sexual orientation, age, marital status, veteran status, disability status, political views or activity, or other applicable legally protected characteristics. We believe that a variety of perspectives will make our teams and business stronger as we work together to transform the traditional banking system.

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 interviewaccommodationslendingclub.com.

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About LendingClub

LendingClub

Financial services company.

501-1,000

Employees

San Francisco

Headquarters

Reviews

3.5

1 reviews

Work Life Balance

3.0

Compensation

3.0

Culture

2.5

Career

2.0

Management

3.0

25%

Recommend to a Friend

Cons

Company reputation/brand perception issues

Not considered top-tier fintech

Grouped with lower-quality competitors

Salary Ranges

523 data points

Mid/L4

Senior/L5

Mid/L4 · Data Engineer

1 reports

$225,152

total / year

Base

$173,040

Stock

-

Bonus

-

$225,152

$225,152

Interview Experience

1 interviews

Difficulty

3.0

/ 5

Duration

21-35 weeks

Interview Process

1

Application Review

2

HR Screen

3

Hiring Manager Interview

4

Technical Assessment

5

Panel Interview

6

Offer

Common Questions

Technical Knowledge

Behavioral/STAR

Past Experience

Case Study

Risk Assessment