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
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
10+ years of experience and a bachelor’s degree in Computer Science, Information Systems, or related field; or equivalent experience
Choosing a digital partner is about more than capabilities — it’s about collaboration and character.
Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments.
At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations.
Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale.
Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact.
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At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward.
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