Senior Data Engineer: Spark, Airflow & AI Pipelines

Aumni; Plano (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

JPMorganChase & Co. is seeking a Data Engineer III in Plano, TX to design and deliver robust data pipelines and architectures that support data engineering lifecycles and AI initiatives. The role emphasizes secure, scalable solutions and collaboration across data science and business teams.

You will build and maintain ETL processes, data models, and data warehouses using Python and SQL, while ensuring data quality and governance in a fast-paced environment.

Qualifications

• Formal training or certification on data engineering concepts.
• 3+ years of experience in end-to-end data engineering lifecycles.
• Experience using AI capabilities to support data engineering workflows with validation.

Responsibilities

• Design, build, and optimize end-to-end data pipelines with Databricks/Spark and AWS.
• Implement and manage workflow orchestration with Airflow.
• Integrate streaming data using Kafka.
• Prepare data for AI/ML initiatives and model deployment.
• Collaborate with data scientists and analysts to deliver data solutions.
• Ensure data quality, security, and governance across the lifecycle.
• Develop ETL processes, data models, and data warehouses.
• Write efficient Python and SQL for data processing and analysis.
• Validate AI-assisted outputs and ensure traceability and auditability.
• Monitor and optimize data workflows for performance and reliability.
• Stay current with data engineering and AI industry practices.

Skills

Databricks

Apache Spark

AWS

Airflow

Kafka

Python

SQL

Data modeling

ETL development

Data warehousing

AI/ML workflows

Security/compliance

Education

Formal data engineering certification

Tools

Databricks

Apache Spark

AWS (S3, Redshift, Lambda)

Airflow

Kafka

Job description

JPMorganChase & Co. is seeking a Data Engineer III in Plano, TX to design and deliver robust data pipelines and architectures that support data engineering lifecycles and AI initiatives. The role emphasizes secure, scalable solutions and collaboration across data science and business teams.

You will build and maintain ETL processes, data models, and data warehouses using Python and SQL, while ensuring data quality and governance in a fast-paced environment.