oracle
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
Key Skills for This Role
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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