Join J.P. Morgan’s Corporate and Investment Bank, a global leader trusted by the world’s most important corporations, governments, and institutions. Be part of a team that manages $21.4 trillion in assets across 100+ countries and 49,000 employees globally. Drive innovation in data engineering, leveraging Snowflake and cloud technologies to deliver impactful solutions.

Job Summary

As a Snowflake Data Engineering Lead within the Cost & Commission Services team, you design, develop, and maintain robust data pipelines and architectures. You drive data governance, performance optimization, and mentor engineers while collaborating with business and technology stakeholders. You ensure scalable, secure, and efficient data solutions that support business objectives and regulatory requirements.

Job Responsibilities

• Design, develop, and maintain scalable data pipelines using Snowflake and cloud solutions.
• Translate complex business requirements into technical solutions meeting data warehousing standards.
• Build and maintain governance processes for data cataloging, ownership, and access control.
• Optimize and refine data processes to improve performance and reliability.
• Collaborate with business, analytics, and project teams to align data solutions with needs.
• Monitor pipelines, perform data quality checks, and enforce best practices.
• Provide mentorship and training on Snowflake best practices to team members.
• Stay up-to-date with advancements in Snowflake and related technologies.
• Drive design and review of test cases, process changes, and manage project scope and deployment.
• Perform advanced quantitative analysis of large datasets to identify business trends.
• Manage Snowflake data sharing, exchange, and ecosystem-specific features.

Required Qualifications, Capabilities and Skills

• Hold a Bachelor’s degree in Computer Science, Information Technology, or related field.
• Demonstrate a minimum of 12 years of experience in data engineering with deep Snowflake expertise.
• Manage teams, including hiring, coaching, performance management, and delivery oversight.
• Apply Agile methodologies, running ceremonies and prioritizing backlogs for continuous improvement.
• Exhibit proficiency in SQL and experience with data pipeline/ETL tools.
• Design and implement large-scale data solutions in cloud environments.
• Communicate complex technical concepts clearly to peers, management, and stakeholders.

Preferred Qualifications, Capabilities and Skills

• Demonstrate deep understanding of data modeling concepts like Star Schema and Data Vault.
• Leverage Snowflake’s advanced features for enhanced data engineering.
• Utilize SQL Servers and write complex SQL queries.
• Apply Alteryx skills, holding Alteryx Designer Core Certification.
• Integrate data visualization tools like Tableau or Qlik View with cloud data environments.
• Collaborate using platforms such as Jira and Confluence.
• Employ Python proficiency for advanced data engineering tasks.