Senior Lead Software Engineer - Python, PySpark, Big Data, Data pipeline, ML/AI

JPMorgan Chase; Plano (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

JPMorgan Chase in Plano, TX is seeking a Senior Lead Software Engineer to drive architecture and delivery of secure, scalable technology products within the Consumer and Community Banking - Risk Technology Portfolio. You will lead agile teams to design, develop, and operate advanced data-driven solutions, mentor engineers, and apply AI-assisted development practices to improve code quality and delivery speed.

Experience with large data, Spark, AWS, and Databricks is highly valued.

Qualifications

• Formal training and certification on software engineering concepts.
• 5+ years of applied software engineering experience.
• 2+ years of leading technologists to solve complex items.
• Hands-on design, development, testing, and operation in large environments.
• Experience with modern programming languages and database querying.
• Experience with AI-assisted software development tools and evaluating AI outputs.
• Understanding of CI/CD, Application Resiliency, and Security.
• Strong knowledge of SQL and data quality at scale.
• Experience with AWS services and Databricks for data pipelines and ML models.
• Familiarity with Spark clusters and large data processing.

Responsibilities

• Executes software solutions, design, development, and troubleshooting with advanced approach.
• Drives AI-assisted engineering practices for code quality, speed, and ops outcomes.
• Applies SDLC tools to drive efficiency and reuse firm technology assets.
• Creates secure, high-quality production code and maintains running algorithms.
• Drives AI/ML delivery best practices alongside software engineering practices.
• Defines architecture for complex deliverables.
• Gathers and analyzes data to visualize and report for continuous improvement.
• Proactively identifies hidden problems and patterns to improve code hygiene.

Skills

Leadership

CI/CD

Agile

SQL

Python

Spark

AWS

Databricks

Data pipelines

ML awareness

Tools

Spark

Databricks

AWS

EMR

EC2

S3

CloudWatch

Airflow

Job description

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorgan Chase within the Consumer and Community Banking - Risk Technology Portfolio team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities:

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets.
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Drive the AI / ML delivery best practices along with software engineering best practices.
• 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.
• Define architecture for series of complex deliverables.
• Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture

Required qualifications, capabilities, and skills:

• Formal training and certification on software engineering concepts and 5+ years applied experience. In addition, 2+ years of experience leading technologists to manage and solve complex technical items within your domain of expertise
• Hands-on practical experience in system design, application development, testing, and operational stability
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• 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.
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Good knowledge of Machine Learning modelling as an engineer
• Experience in working with one or more programming language(s) and framework(s) (i.e., Python, PySpark, Big Data, Data pipeline, Machine Learning, etc.)
• Strong SQL skills with ability to validate features and data quality at scale
• Experience configuring and optimizing Spark clusters for processing large data.
• Hands-on experience working with AWS services including EMR, EC2, S3, and CloudWatch
• Working knowledge on Databricks in creating Data Pipelines, Machine learning models deployment.

Preferred qualifications, skills, and capabilities:

• Expertise with programming languages like Java, python
• Experience in Cloud Technologies (i.e., AWS - Databricks preferred)
• Experience with serving high volume, High availability & ultra low latency API solutions with Java - Spring Boot applications
• Awareness with Python Machine Learning libraries and ecosystems (i.e., Pandas, Numpy, etc.)
• AWS certifications (e.g. Solutions Architect Associate)
• Exposure to workflow orchestration tools (e.g. Apache Airflow)
• Familiarity with modern LLM techniques