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- Tasks: Lead software engineering projects, develop secure microservices, and optimise big data pipelines.
- Company: Join JPMorganChase, a leader in global finance technology with a focus on innovation.
- Benefits: Competitive salary, diverse culture, and opportunities for professional growth.
- Other info: Inclusive team culture with mentorship and continuous improvement opportunities.
- Why this job: Make an impact in finance tech while working with cutting-edge tools and technologies.
- Qualifications: Strong experience in Python, Java, and AWS; passion for data engineering and software development.
The predicted salary is between 80000 - 100000 ÂŁ per year.
As a Senior Lead Software Engineer (Python/Java, Spring, API, AWS) at JPMorganChase in Global Finance Technology, you’ll build secure, scalable solutions, write production code and tests, review code, and pair program. In Regulatory Reporting, you’ll develop and optimize Python/PySpark big data pipelines across asset classes.
Job Responsibilities
- Lead by example: contribute production‑quality code daily, write tests, perform code reviews, and pair program.
- Design and deliver secure, high‑quality microservices and web applications with Java/Spring Boot and React; own deep debugging, root‑cause analysis, and performance tuning for high-availability services.
- Own end‑to‑end build‑and‑run: design, implement, test, deploy, and operate services (“you build it, you run it”).
- Design, develop, and maintain robust big data pipelines using Python and PySpark on Databricks platform on AWS, optimizing complex queries and data processing workflows to ensure efficient performance at scale.
- Provide technical leadership and act as SME for microservices, CI/CD, observability, performance engineering, and data modelling.
- Champion SDLC practices: test automation, CI/CD, security‑by‑default, quality gates, and disciplined change management.
- Embed non‑functional requirements (security, scalability, reliability, observability, cost) into designs; implement logging, metrics, tracing, SLOs, error budgets, alerting, and runbooks.
- Foster an inclusive team culture; mentor engineers and drive continuous improvement and craftsmanship.
- Participate in the full Software Development Life Cycle (SDLC), including requirements gathering, design, development, testing, deployment, and maintenance, working with our partners Product Owners and end users to support their business use cases.
- Implement data quality checks, monitoring, and alerting mechanisms to ensure data accuracy and pipeline reliability and act as both Production Support and SRE function as part of daily responsibilities.
- Hands‑on use of AI coding assistants to accelerate delivery (e.g., Claude Code/Claude CoWork, IDE Copilot): prompt design, code/test generation, refactoring, and documentation synthesis; ability to validate outputs for correctness, security, performance, and licensing compliance.
Required Qualifications, Capabilities, And Skills
- Strong hands‑on experience in data engineering or related roles.
- Strong proficiency in Python and PySpark for large‑scale data processing.
- Advanced proficiency in Java and Spring Boot; strong fundamentals, design patterns, and secure coding.
- Full‑stack delivery with React (component/state management) and secure RESTful API design.
- Demonstrated experience with AWS, Databricks and Apache Spark ecosystem.
- Reliability and performance engineering: concurrency, thread management, caching, and resiliency patterns (circuit breakers, retries, backoff), with cost awareness.
- Proven track record shipping and operating production systems; comfortable troubleshooting in Kubernetes, CI/CD, and cloud environments.
- Relational and NoSQL databases: schema design, performance tuning, and secure data access.
- Experience with AWS cloud services (S3, ECS, SNS/SQS, Lambda, etc.).
- Strong analytical skills with ability to investigate data issues, identify root causes, and implement solutions.
- Experience with the complete SDLC, Jules/Jenkins, Spinnaker, Sonar and Agile methodologies.
- Understanding of financial services industry and regulatory requirements.
- Databricks or AWS certifications.
- Automated testing frameworks, e.g. Playwright, Cucumber, Gherkin etc.
- Experience with Parquet, JSON, CSV, Avro, Delta Lake.
Preferred Qualifications, Capabilities, And Skills
- Understanding of regulatory finance/external reporting (workflows, aggregations, reconciliations, controls).
- Cloud certifications; proven cloud‑native delivery on AWS.
- Experience with large‑scale distributed systems, event‑driven architectures, and messaging/streaming patterns.
- Observability/SRE depth: telemetry pipelines, alerting strategies, incident response, post‑mortems, and continuous improvement.
- Experience with data orchestration tools (Airflow, Step Functions, etc.).
Senior Lead Software Engineer - Databricks & Python employer: JPMorganChase
Contact Detail:
JPMorganChase Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Lead Software Engineer - Databricks & Python
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage in online communities. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, Databricks, and AWS. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the company’s tech stack. Practice coding challenges and be ready to discuss your past experiences with big data pipelines and microservices.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior Lead Software Engineer - Databricks & Python
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your Python and Databricks expertise, and don’t forget to mention any relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for the Senior Lead Software Engineer role. Share your passion for building scalable solutions and how you’ve led teams in the past.
Showcase Your Technical Skills: In your application, be specific about your technical skills. Mention your experience with AWS, microservices, and CI/CD practices. We want to see how you can contribute to our team right from the get-go!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, we love seeing candidates who take that extra step!
How to prepare for a job interview at JPMorganChase
✨Know Your Tech Stack
Make sure you’re well-versed in Python, PySpark, Java, and Spring Boot. Brush up on your knowledge of AWS and Databricks too. Be ready to discuss how you've used these technologies in past projects, especially in building scalable solutions.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex data issues or performance tuning challenges. Highlight your experience with debugging and root-cause analysis, as this will demonstrate your ability to handle high-availability services.
✨Emphasise Team Collaboration
Since mentoring and fostering an inclusive culture is key, be prepared to discuss how you’ve collaborated with others in your previous roles. Share experiences where you’ve led by example, conducted code reviews, or pair programmed to enhance team performance.
✨Understand the Business Context
Familiarise yourself with the financial services industry and regulatory requirements. Being able to connect your technical skills to business use cases will show that you understand the bigger picture and can contribute effectively to the team.