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Software Engineer III - Python/PySpark/Databricks/AWS

JPMorgan Chase
Wilmington, USA
Full-time
Mid · 3+ years experience
Onsite
Discovered 1 weeks ago
airflowawsaws-gluedatabricksdelta-lakepython

Full Job Posting

Job responsibilities

  • Developing and optimizing data pipelines and workflows to support data integration, transformation, and analysis
  • Implementing best practices for data management, ensuring data quality, security, and compliance
  • Writing secure, high-quality production code following AWS best practices, and deploying efficiently using CI/CD pipelines
  • Creating architecture and design documents for complex applications, ensuring software code meets design constraints
  • Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
  • Identifying hidden issues and patterns in data to enhance coding practices and system architecture

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 3+ years applied experience
  • Experience with Spark and SQL
  • Expertise in Lakehouse/Delta Lake architecture, system design, application development, testing, and ensuring operational stability
  • Strong programming skills in Python/PySpark, Databricks, AWS Glue, S3, SQS/SNS, Lambda etc., SQL
  • Proficient in orchestration using Airflow
  • In-depth knowledge of Big Data and data warehousing concepts
  • Experience with CI/CD processes
  • Solid understanding of agile methodologies, including DevOps practices, application resiliency, and security measures
  • Proven expertise in software applications and technical processes within a specialized technical domain
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.

Preferred qualifications, capabilities, and skills

  • Familiarity with Snowflake, Terraform and LLM
  • Familiarity with Data Observability, Data Quality, Query Optimization & Cost Optimization
  • AWS certifications such as SAA, Associate Developer, Data Analytics Specialty, or Databricks certification

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