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Software Engineer II - Python, Databricks, ETL

JPMorgan Chase
Chicago, USA
Full-time
Junior · 2+ years experience
Onsite
Discovered 2 weeks ago
airflowawsdatabrickspythonsqlterraform

Full Job Posting

Job responsibilities

  • Design, develop, and maintain scalable data pipelines and ETL processes to support data integration and analytics.
  • Frequently utilizes SQL and understands NoSQL databases and their niche in the marketplace
  • Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards.
  • Contribute to data modernization efforts by leveraging cloud solutions and optimizing data processing workflows
  • 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
  • Perform data extraction and implement complex data transformation logic to meet business requirements
  • Ensure data availability and accuracy for analytical purposes, implement best practices for data engineering, ensuring data quality, reliability, and performance, monitor and executes data quality checks.
  • Identify opportunities for process automation within data engineering workflows
  • Implement data orchestration and workflow automation using AWS step, Event Bridge
  • Use Terraform for infrastructure provisioning and management, ensuring a robust and scalable data infrastructure.

Required qualifications, capabilities, and skills

  • Formal training or certification on Data Engineering concepts and 2+ years applied experience
  • Experience working with modern Lakehouse: Databricks
  • Experience in Python, Pyspark, AWS, Databricks, Gen/Agentic AI skills, MCP, Elastic search, RESTAPI
  • Proficient in SQL coding (e.g., joins and aggregations) including RDBMS skills
  • Working understanding of SQL databases
  • Experience in building and optimizing data pipelines, architectures, and data sets ( Glue or Data bricks ETL)
  • Experience in developing ETL process and workflows for streaming data from heterogeneous data sources
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.

Preferred qualifications, capabilities, and skills

  • Strong analytical and problem-solving skills, with attention to detail.
  • Experience building Pipeline on AWS using Terraform and using CI/CD pipelines
  • Knowledge of RDBMS like Aurora
  • Experience with data pipeline and workflow management tools (Airflow, etc.)

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