Data Software Engineer III

Overview

Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.

As a Software Engineer III at JPMorgan

Chase within the Consumer & Community Banking Open Banking team, you serve as a seasoned member of an agile team to design and deliver trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. You are responsible for developing, testing, and maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives.

• Supports review of controls to ensure sufficient protection of enterprise data
• Advises and makes custom configuration changes in one to two tools to generate a product at the business or customer request
• Updates logical or physical data models based on new use cases
• Frequently uses SQL and understands No
  
  SQL databases and their niche in the marketplace
• Performing ETL and analysis of data
• Adds to team culture of diversity, opportunity, inclusion, and respect

• Formal training or certification on software engineering concepts and 3+ years applied experience
• Advanced at SQL (e.g., joins and aggregations)
• Working understanding of No
  
  SQL databases
• Experience customizing changes in a tool to generate product
• Strong organizational, problem-solving, and critical thinking skills;
  Strong documentation skills
• Proficiency in Python or Java
• Cluster Computing frameworks:
  Proficiency in Spark
• AWS Data Services:
  Proficiency in Lake formation, Glue ETL (or) EMR, S3, Glue Catalog, Athena, Kinesis (or) MSK, Airflow (or) Lambda + Step Functions + Event Bridge
• Data De/Serialization:
  Expertise in atleast 2 of the formats:
  Parquet, Iceberg, AVRO, JSON-LD
• Dev Ops:
  Linux Scripting, Jenkins, Git, CI/CD, JIRA, TDD
• AWS Data Security:
  Good Understanding of security concepts such as:
  Lake formation, IAM, Service roles, Encryption, KMS, Secrets Manager

• Experience across the data lifecycle
• Significant experience with statistical data analysis and ability to determine appropriate tools and data patterns to perform analysis