Senior Manager of Data Engineering, Lending Club

• You’re passionate about building modern data platforms, leading high-performing teams, and solving complex data challenges at scale
• 8+ years of experience in data or software engineering, including 3+ years in a technical leadership or people management role
• Proven ability to lead, develop, and scale high-performing data engineering teams while remaining hands-on with architecture and design
• Deep expertise in distributed data systems (Hadoop, Spark, Hive, Kafka), orchestration frameworks (Airflow/Dagster), DBT, and modern data platforms (Databricks, Snowflake)
• Strong coding background in Python and experience building production-grade pipelines
• Hands-on experience with cloud platforms (AWS preferred) and cloud cost optimization
• Skilled in Git, CI/CD, Agile, and test-driven development
• Excellent communication and stakeholder management skills, with the ability to bridge technical and business needs
• Committed to simplicity, scalability, and delivering high-quality, reliable, and efficient data solutions

Desirable

• We’re looking for a Sr Manager, Data Engineering to help scale our data capabilities across batch processing, real-time streaming, pipeline orchestration, data lake management, and cataloging
• In this role, you’ll lead a talented team of engineers and use your expertise in big data, design thinking, and modern analytics to build the libraries, frameworks, and pipelines that power our data ecosystem
• Lead and grow a team of data engineers building systems, libraries, and frameworks that power batch and streaming data and ML applications
• Partner with Product, Business, and Engineering teams to align data solutions with strategic priorities and deliver measurable business impact
• Define and evolve the technical vision for LendingClub’s modern data stack, including Hadoop, Spark, DBT, Airflow/Dagster, Atlan, Trino, Databricks, Snowflake, and AWS
• Design and deliver scalable, reliable data pipelines that transform raw data into trusted, business-ready datasets
• Champion data quality, observability, governance, and lineage to ensure data is accurate, compliant, and dependable
• Identify opportunities for automation, performance optimization, cost efficiency, and scalability across the data ecosystem
• Establish and promote best practices for software development, CI/CD, and operational excellence
• Provide technical leadership in resolving production issues, driving root-cause analysis, and improving system resiliency
• Mentor and inspire team members, fostering a culture of collaboration, continuous learning, and delivery excellence