Our mission at LendingClub is to empower those who strive to achieve better

financial health. Data intelligence team plays a crucial role in achieving our

mission.

We are seeking a Lear Data Modeling Engineer for our Data team to provide data

modeling, data processing, and pipeline orchestration capabilities. You'll be part of

the Data Intelligence organization that helps drive business decisions using data.

You will have the opportunity to use your expertise in data modeling, software

development, design thinking, and analytical skills to build scalable data pipelines,

robust data models, and high-quality data products leveraging our PB-scale data.

This role is primarily focused on data modeling, with strong ownership of building

and supporting the data pipelines and systems that operationalize those models.

You will be responsible for designing and evolving data models in a centralized

data warehouse, ensuring they are scalable, performant, and aligned with business

needs. In parallel, you will contribute to engineering development to ensure

reliable data ingestion, transformation, and delivery.

You will also play a key role in driving data standardization efforts, establishing

consistent definitions, modeling patterns, and data quality practices across the

organization.

What You'll Do

Design, develop, and maintain scalable, high-quality data models in a

centralized data warehouse (primary focus)

Translate business requirements into well-structured, reusable data models

that support analytics and downstream applications

Define and enforce data modeling standards, naming conventions, and best

practices across domains

Lead and contribute to data standardization initiatives to ensure

consistency and interoperability of data assets

Build and maintain data pipelines that support and operationalize data

models (ingestion, transformation, and delivery)

Develop pipelines that transform raw data into clean, well-modeled,

analytics-ready datasets

Collaborate with Product, Engineering, and Program teams to deliver endto-end data solutions (models + pipelines)
Optimize data models and pipelines for performance, scalability, and cost

efficiency

Implement processes for data validation, quality monitoring, and reliability
Write high-quality, testable code; adopt TDD and contribute to engineering

documentation and best practices

Perform root cause analysis on data and pipeline issues to improve system

robustness

About You

10+ years of experience and a bachelor's degree in Computer Science,

Information Systems, or related field; or equivalent experience

Strong expertise in data modeling (dimensional modeling, warehouse

design, normalization techniques)

Proven experience designing and implementing data models in

centralized/cloud data warehouses (Databricks, Snowflake, Redshift, etc.)

Solid experience in data engineering and pipeline development to support

modeled data layers

5+ years of experience with Databricks and DBT
Experience with orchestration tools such as Airflow or Dagster
In-depth experience with distributed systems such as Spark
Strong programming skills (Java, Scala, Python) with experience building

production-grade data pipelines

Experience with AWS cloud services (EC2, EMR, RDS)
Strong understanding of data standardization, data governance, and data

quality best practices

Experience with Git, JIRA, Jenkins, and CI/CD pipelines
Experience working with cross-functional teams in a dynamic environment
You are passionate about data modeling and designing scalable, wellstructured datasets
You are equally comfortable implementing pipelines that bring those

models to life

You think in terms of data consistency, reusability, and long-term

maintainability

You value clean design, simplicity, and high-quality engineering practices
You have a track record of delivering reliable, well-modeled, production - ready data solutions

Lead Data Engineer - Data Modeler