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Today

Lead Data Engineer

JPMorganChase Plano, TX

Plano, TX

Today

Full time Big Data Data Architecture Data Engineer

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Job Description

JPMorganChase offers a comprehensive benefits package and on-site wellness resources for this Plano, Texas based role. As a Lead Data Engineer on the Consumer and Community Banking team, you will design scalable data pipelines and architectures, drive data governance and performance optimization, and mentor engineers to deliver secure, compliant data solutions.

Benefits

Base salary
Commission-based pay
Discretionary incentive compensation (cash)
Forfeitable equity
Health care coverage
On-site health and wellness centers
Retirement savings plan
Backup childcare
Tuition reimbursement
Mental health support
Financial coaching

Responsibilities

Architect and implement scalable batch and streaming pipelines with strong performance, fault tolerance, and observability
Develop and manage workflow orchestration to schedule, monitor, and control data movement and transformations
Translate complex business requirements into technical designs that align with data lake and data warehousing standards
Utilize enterprise AI capabilities to speed up data pipeline design analysis and documentation, validating outputs and ensuring data handling aligns with sensitivity and security policies
Adopt reuse-first, AI-assisted practices to strengthen SDLC quality routines for data pipelines, including test generation and control validation, ensuring traceability and compliance with resiliency and security expectations
Build and sustain governance processes for data modeling, cataloging, ownership, and access control
Mentor teammates on data publication best practices and guide the team's 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 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 experience in data engineering with deep AWS, data lake, and Snowflake expertise
Hands-on experience with modern data lake and warehousing technologies (eg, Redshift, BigQuery, Snowflake) and processing engines such as Spark, Flink, or Trino
Experience applying Agile methodologies, leading ceremonies, and prioritizing backlogs for continuous improvement
Proficiency in SQL and experience with data pipeline and ETL tools
Demonstrated use of 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 before use, escalate when uncertain, and follow data handling requirements
Experience building streaming pipelines using Kafka, Pub/Sub, or similar messaging systems
Experience with large-scale distributed data processing and performance tuning
Design and implement large-scale data solutions in cloud environments

Technologies

AWS
Snowflake
Redshift
BigQuery
Spark
Flink
Trino
Kafka
Pub/Sub
SQL

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