Software Engineer III- Data Engineer(Python, Databricks and AWS)

JPMorgan Chase & Co. • Plano, TX

3h

About The Position

As a Data Engineer III at JPMorganChase within the Corporate Sector, you will serve as a seasoned member of an agile team designing and delivering trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. You will design, build, and maintain robust data pipelines and architectures across the data engineering lifecycle, working with cross-functional teams to deliver scalable solutions that drive business insights and support advanced analytics, including AI initiatives.

The role involves developing end-to-end pipelines with Databricks, Apache Spark, and AWS; orchestrating workflows with Airflow; integrating streaming data with Kafka; and creating ETL processes, data models, and data warehouses. You will use Python and SQL, support AI and machine-learning initiatives through data preparation and engineering, and monitor and optimize workflows for reliability and performance. The position also involves using enterprise-authorized AI capabilities to assist with analysis, documentation, and SDLC-quality routines, while validating outputs and following data sensitivity, security, traceability, and auditability requirements.

Requirements

• Formal training or certification in data engineering concepts and at least 3 years of applied experience.
• Proven experience across the full data engineering lifecycle, from ingestion to production.
• Demonstrated experience using enterprise-authorized AI capabilities in 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, such as query suggestions, test ideas, or model change summaries, before use; escalate when uncertain and follow data-handling requirements.
• Strong hands-on expertise with Databricks, Apache Spark, AWS services such as S3, Redshift, and Lambda, Airflow, and Kafka.
• Proficiency in Python and SQL for data manipulation and analysis.
• Experience with data modeling, ETL development, and data warehousing.
• Familiarity with AI/ML workflows and supporting data pipelines for machine learning.
• Excellent problem-solving skills and attention to detail.
• Strong communication and teamwork abilities.

Nice To Haves

• Certifications in relevant technologies such as AWS, Databricks, or Spark.
• Experience with containerization technologies such as Docker and Kubernetes.
• Knowledge of data governance and compliance standards.
• Exposure to big data tools and frameworks.
• Ability to work in a fast-paced, agile environment.

Responsibilities

• Design, develop, and optimize end-to-end data pipelines using Databricks, Apache Spark, and AWS cloud services.
• Implement and manage workflow orchestration with Airflow.
• Integrate and process streaming data using Kafka.
• Use enterprise-authorized AI capabilities to accelerate data pipeline and design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements.
• Collaborate with data scientists, analysts, and business stakeholders to understand requirements and deliver high-quality data solutions.
• Ensure data quality, integrity, and security across all stages of the data lifecycle.
• Develop and maintain ETL processes, data models, and data warehouses.
• Write efficient, maintainable Python and SQL code for data processing and analysis.
• Apply reuse-first, AI-assisted practices to strengthen SDLC-quality routines for data pipelines, such as test generation and control validation, ensuring traceability, auditability, resiliency, and security alignment.
• Support AI and machine-learning initiatives by preparing and engineering data for model development and deployment.
• Monitor, troubleshoot, and optimize data workflows for performance and reliability.
• Stay current with industry best practices and emerging technologies in data engineering and AI.

Benefits

• Competitive total rewards package, including base salary determined by role, experience, skill set, and location.
• Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed