Software Engineer II

As a Software Engineer II at JPMorgan Chase within  CCB, you will design, build, and optimize scalable data pipelines and architectures on AWS, leveraging Data Lake, Snowflake, and distributed processing technologies.

• Design, develop, and maintain scalable data pipelines and ETL processes on AWS (S3, Glue, Lambda, Redshift, etc.) using Python and Spark.
• Architect and implement Data Lake solutions, ensuring efficient data ingestion, storage, and retrieval.
• Integrate and manage Snowflake environments for data warehousing and analytics.
• Develop and optimize distributed data processing workflows using Apache Spark (PySpark).
• Collaborate with AI/ML teams to enable data-driven models and solutions, supporting feature engineering and model deployment.
• Leverage AI coding assistants such as Copilot and Claude to accelerate development, improve code quality, and automate repetitive tasks.
• Optimize data workflows for performance, reliability, and cost efficiency.
• Ensure data quality, governance, and security across all platforms.
• Automate data processing tasks using Python, Spark, and AWS-native tools.
• Monitor, troubleshoot, and resolve issues in data pipelines and infrastructure.
• Document technical solutions and provide knowledge transfer to team members.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 5+ years of experience in data engineering, with hands-on AWS experience.
• Strong proficiency in AWS services: S3, Glue, Lambda, Redshift, IAM, etc.
• Experience with Data Lake architecture and implementation.
• Expertise in Snowflake data warehousing, including schema design, performance tuning, and security.
• Advanced programming skills in Python and SQL.
• Hands-on experience with Apache Spark (preferably PySpark) for large-scale data processing.
• Familiarity with AI/ML concepts and workflows; experience supporting data science teams.
• Experience using AI coding assistants such as GitHub Copilot and Claude to enhance productivity and code quality.
• Knowledge of data governance, security, and compliance best practices.
• Excellent problem-solving and communication skills.

• Experience with workflow/orchestration tools such as Apache Airflow.
• Exposure to DevOps practices and CI/CD pipelines.
• AWS certification (e.g., AWS Certified Data Analytics, Solutions Architect).
• Experience with real-time data processing and streaming (e.g., Kinesis, Kafka).
• Familiarity with BI tools (e.g., Tableau, Power BI).