Lead Data Engineer

JPMorgan Chase is hiring a Lead Data Engineer for the Consumer and Community Banking organization in Plano, TX. The role focuses on designing, building, and maintaining scalable batch and streaming data platforms that support business needs while meeting governance, performance, and regulatory expectations.

Key Responsibilities

• Design, build, maintain, and optimize scalable batch and streaming data pipelines with performance, fault tolerance, and observability in mind.
• Develop and operate workflow orchestration to schedule, monitor, and manage data movement and transformation workflows.
• Convert complex business requirements into technical solutions aligned to data lake and data warehousing standards.
• Use enterprise-authorized AI capabilities within the work environment to accelerate data pipeline design and documentation, including validating outputs and handling data according to sensitivity and security requirements.
• Apply reuse-first, AI-assisted practices to strengthen SDLC-quality processes for data pipelines, including test generation and control validation, with traceability and auditability aligned to resiliency and security expectations.
• Build and maintain governance processes for data modeling, cataloging, ownership, and access control.
• Provide mentorship and training on data publication best practices, leading technical direction through standards, reviews, and knowledge sharing.
• Stay current with advancements in AWS Data Lake, Snowflake Data Warehouse, and related technologies.
• Perform advanced quantitative analysis on large datasets to identify business trends.
• Manage data sharing and exchange, including ecosystem-specific features.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• 5+ years of data engineering experience with deep expertise in AWS, Data Lake, and Snowflake.
• Hands-on experience with modern data lake and warehousing technologies, including Redshift, BigQuery, and Snowflake, as well as engines such as Spark, Flink, or Trino.
• Experience applying Agile methodologies, including running ceremonies and prioritizing backlogs for continuous improvement.
• Proficiency in SQL and experience with data pipeline and ETL tools.
• Demonstrated ability to use enterprise-authorized AI capabilities within the work environment to support data engineering workflows, with strong validation habits and awareness of data sensitivity.
• Ability to review and validate AI-assisted outputs (for example, query suggestions, test ideas, or model change summaries) before use, escalating when uncertain and following data handling requirements.
• Experience designing and building streaming pipelines using Kafka, Pub/Sub, or similar messaging systems.
• Experience with large-scale distributed data processing and performance tuning.
• Ability to design and implement large-scale data solutions in cloud environments.

Preferred Qualifications

• Experience with data modeling in Erwin.
• Experience with table formats such as Iceberg and Hudi.

Technology Focus

• AWS Data Lake, Snowflake Data Warehouse
• Redshift, BigQuery, Snowflake
• Spark, Flink, Trino
• SQL
• Kafka, Pub/Sub
• Erwin
• Iceberg, Hudi

Role Location and Experience

Location: Plano, TX 75024 (onsite)

Minimum Experience: 5 years