Job DescriptionWe have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Software Engineer at JPMorganChase within the Corporate Sector - Infrastructure Platforms - Data and Speciaity Services 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. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
This lead engineer will be focused on designing, automating, and operating scalable ETL/data transformation pipelines to production. They will work with stakeholders to gather requirements, build and optimize Spark-based batch/real-time workflows and data lake tables (Iceberg/Delta), contribute to platform/SDK infrastructure, improve cost and reliability through monitoring (Grafana/Prometheus) and CI/CD, and mentor junior engineers. Heavy experience with Spark (Scala/Python/Java), distributed data stores (HBase/Cassandra), cloud data tooling (Azure/AWS), and API delivery via Spring Boot/Docker with Git-based collaboration would be ideal.
Job responsibilities- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Review, understand, code, optimize, and automate existing one-off data transformation pipelines into discrete, scalable tasks
- Plan, design, and implement data transformation pipelines and monitor operations of the data platform in a production environment
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems and also plan, design, and implement data transformation pipeline to monitor the operations of data platforms in a production environment
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review / refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation, collaborating with internal clients and service delivery engineers to identify data needs and intended workflows, and troubleshoot to find workable solutions
- Gather, analyze, and document detailed technical requirements to design and implement solutions, and disseminate information to guide other engineers
- Contribute code to the underlying infrastructure, software development kits, and platforms being built to support bespoke data transformation pipelines and enable predictive models to be produced and run at scale
- Identify engineering opportunities to optimize operational effort and running costs of the data platform
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
- Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
- Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies, and mentor junior engineering staff - providing guidance on day-to-day code development work
- Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills- Formal training or certification on Software engineering concepts and 5+ years applied experience
- Advanced in one or more programming language(s) and framework(s), i.e., Python, Java, Scala, Apache Spark, Databricks, Grafana, Prometheus, Elasticsearch, Cloudwatch, Spring Boot API, and containers
- Implementing low-latency, scalable data operations and supporting real-time lookups, updates, and analytics using Apache HBase and Apache Cassandra
- Build, design and implement scalable ETL pipelines to process structured and semi-structured data and implement partitioning within Hadoop-based architectures
- Managing large-scale data lake tables in Iceberg format and proficiency in automation and continuous delivery methods also supporting real-time and batch data ingestion, data cleansing, and transformation, and feature extraction on Spark
- Implementing ACID-compliant data operations and enabling schema evolution using Delta table structures
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
- Configuring and maintaining Grafana dashboards integrated with Prometheus, Elasticsearch, or CloudWatch to monitor pipeline performance, API services, and system health in real time
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security, also with documenting data workflows, Spring Boot API specifications, CI/CD processes, Grafana configurations, and cloud architecture using Confluence
- Demonstrated proficiency in software applications and technical processes within a technical discipline and proficient in all aspects of the Software Development Life Cycle (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
Preferred qualifications, capabilities, and skills- In-depth knowledge of the financial services industry and their IT systems
- Practical cloud native experience
- Creating and deploying RESTful APIs using Spring Boot in Docker containers to deliver processed data access and operational insights
- Managing source code to maintain structured development workflows, version control, and team collaboration using Git with GitHub and Bitbucket
- Building, deploying, and managing scalable data engineering pipelines and analytics infrastructure using Azure Data Factory, Databricks, or AWS tools such as EC2, S3, EMR, Lambda, Glue, IAM, or CloudWatch
About UsJPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. 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. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include 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. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About the TeamOur Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.
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