Lead Data Engineer

JPMorgan Chase is hiring a Lead Data Engineer for its Consumer and Community Banking organization in Plano, TX (onsite). In this role, you will design, develop, and maintain data pipelines and architectures that support scalable, secure, and efficient analytics across the business while aligning to operational and regulatory expectations.

You will lead technical delivery across batch and streaming systems, strengthen data governance and stewardship, and partner with teams to turn complex requirements into standards-compliant data lake and warehouse implementations.

What you’ll do

• Design, build, maintain, and optimize scalable batch and streaming data pipelines with performance, fault tolerance, and observability.
• Develop and operate workflow orchestration to schedule, monitor, and manage data movement and transformations.
• Convert complex business needs into technical solutions that meet data lake and data warehousing standards.
• Use enterprise-authorized AI capabilities within the work environment to accelerate pipeline and design analysis and documentation, while validating outputs and applying data sensitivity and security handling requirements.
• Apply reuse-first, AI-assisted practices to improve SDLC-quality routines for data pipelines, including test generation and control validation, with traceability/auditability and alignment 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, and lead the team’s technical direction through standards, reviews, and knowledge sharing.
• Stay current on advancements in AWS Data Lake, Snowflake, and related technologies.
• Perform advanced quantitative analysis of large datasets to identify business trends.
• Manage data sharing, exchange, and ecosystem-specific features.

Requirements

• 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, Snowflake, and engines such as Spark, Flink, or Trino.
• Experience applying Agile methodologies, running ceremonies, and prioritizing backlogs for continuous improvement.
• Proficiency in SQL and experience with data pipeline/ETL tools.
• Demonstrated experience using enterprise-authorized AI capabilities to support data engineering workflows, with strong validation habits and awareness of data sensitivity.
• Ability to review and validate AI-assisted outputs (such as 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.
• Capability to design and implement large-scale data solutions in cloud environments.

Technologies

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

Preferred qualifications, capabilities, and skills

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

Location: Plano, TX 75024 (onsite). Experience: 5+ years.