Software Engineer II - Python, Databricks, ETL

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

Preferred

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.)

Benefits

Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.

Based on eligibility: comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more.

Glassdoor

3.9

JPMorganChase is a financial services company providing banking, investment, financial management, and related services. It is a sub-organization of PricingDirect.

New York, New York, USA

https://www.jpmorganchase.com

Distribution of Different Job Fields Receiving Sponsorship

69

Represents job field similar to this job

Engineering and Development

Management and Executive

Accounting and Finance

Customer Service and Support

Product Management

Legal and Compliance

Marketing

Sales

Creatives and Design

Human Resources

Public Sector and Government

Trends of Total Sponsorships

*2026

(2734)

2025

(3470)

2024

(3469)

2023

(3395)

Qualifications

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

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.)

Required skills

Data Engineering, Databricks, Python, PySpark, AWS, SQL, ETL, Data Pipelines, Streaming Data Processing, Terraform, CI/CD, GenAI and Agentic AI, MCP, Elasticsearch, REST APIs, Amazon Aurora, Apache Airflow

Preferred skills

Knowledge of RDBMS like Aurora

Experience

2+ years